Company Background

Our client is a global technology company transforming the way brands and agencies make marketing decisions. Its platform enables marketers to plan and activate cross-channel, programmatic media campaigns using real-time research, proprietary audience data, advanced analytics, and more than 150 integrated partners including Facebook, Instagram, Pinterest, Snapchat, and Twitter. The company operates across North America, Europe, the Middle East, Asia, and Australia.

Project Description

As a member of the DevOps team, you will be responsible for delivering solutions to your assigned team and scalable, reusable solutions across the entire engineering organization. You will operate infrastructure and ensure services are monitored, reliable, automated, and scalable, supporting tasks from server provisioning and application deployments to troubleshooting. You will also help bridge the gap between development and operations, collaborating across engineering and business teams.

Technologies

• AWS
• Kubernetes
• Linux admin
• OpenTelemetry/Grafana/Prometheus/Elasticsearch
• CI/CD
• ArgoCD
• Bash/Python
• Ansible/Chef
• GitLab
• Airflow
• Spark

What You'll Do

• Contribute to the implementation and design of systems and networks used to operate production infrastructure with a focus on automation;
• Collaborate with developers on operations-related issues, providing support and guidance;
• Develop tools to monitor infrastructure and custom applications;
• Troubleshoot issues across the entire stack;
• Document system design and application operation procedures;
• Build, monitor and tune production systems;

Job Requirements

• Experience with or knowledge of AWS and physical infrastructure (other cloud is a plus);
• Experience with or knowledge of automation tools (Terraform or Ansible);
• Troubleshooting skills and experience with Linux;
• Understanding of Linux, networking, and internet fundamentals;
• Understanding of monitoring infrastructure and applications (e.g. Grafana, Prometheus, InfluxDB);
• Scripting skills in one or more of the following: Bash, Python;
• Experience with containers and orchestration tools such as Docker and Kubernetes (or similar);
• Familiarity with CI/CD tools (e.g. GitLab CI, GitHub Actions, Jenkins);
• Confident use of Git, including branching, pull requests, and code review;
• Basic understanding of security concepts, including secrets management, IAM, and HTTPS/TLS;
• Ability to work with logs and identify the root cause of failures;
• Ability to work independently and deliver tasks with minimal supervision;
• Readiness to participate in on-call / shift duties on a rotating schedule;
• English: B1+ level;

Nice To Have

• Experience with highly loaded production systems;
• Experience with support services such as Consul, Zookeeper & ELK;
• Experience with noSQL solutions (Couchbase a plus);
• Experience with big data systems (EMR, Spark & Hive a plus);

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.

Please complete the attached Internal Transfer Request Form and submit.  

Please make sure to apply with your Coupang e-mail address.  

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.

Role Overview

As our Staff Machine Learning Engineer for Coupang Media Group, Ads Quality, you will be responsible for developing, designing machine learning models, optimization algorithms and new product features for our advertising platform. 

The Coupang Media Group (CMG) is responsible for providing vendors that sell their products on Coupang a host of marketing products and services.  We launched Product Ads performance advertising marketplace late in 2018.  We have grown rapidly to over 10,000 active advertisers and 150M daily ad impressions in only 5 months’ time. Our group is responsible for advertising brands and products inside our e-commerce website. To get an idea of how valuable that is, both Alibaba and Amazon make more money on advertising than on selling products.  

This is an opportunity to be part of building up a new development organization with strong revenue potential inside a successful company. We’re building full-stack engineering teams to handle large scale advertising problems, including real-time behavioral targeting, auctioning and bidding systems and search based advertising. 

We are in the growth phase of the organization, so you’ll be a part of managing the transition from growth phase to enterprise processes. 

In this role you will be responsible for innovating and building our new ad quality stack for our ads platform  and eventually extend it into a full ad exchange, DSP, and SSP. We currently handle about 1bn impressions per day from internal traffic alone. 

What You Will do

• Design features and build large-scale machine learning models and systems to improve ad targeting, relevance, ranking, and engagement 
• Design and implement large-scale ML systems for search ranking, semantic retrieval, query understanding, and personalized product discovery using state-of-the-art techniques such as transformer-based models, contrastive learning, and vector search
• Drive innovation in search relevance and user intent modeling using large language models (LLMs), embedding-based retrieval, and multi-modal learning
• Build and optimize ML pipelines using tools such as Apache Spark, Airflow, Kubeflow, and MLflow, ensuring reproducibility, scalability, and operational excellence
• Define and track key performance metrics to evaluate model impact and identify high[1]leverage opportunities for improvement
• Collaborate cross-functionally with product, engineering, and data science teams to align technical solutions with business goals and customer experience
• Mentor and grow engineering talent, fostering a culture of technical excellence, experimentation and continuous learning

Basic Qualifications

• Bachelor's degree in computer science, electrical engineering, mathematics, statistics or closely related fields
• 4 years of professional experience in applied machine learning
• Experience in machine learning, deep learning, and statistical modeling
• Proficiency in Python and/or Java, with experience in building production grade ML systems

Preferred Qualifications

• Master’s or PhD in relevant technical fields
• Experience with search systems, information retrieval or recommendation engines
• Experience with LLMs, embeddings, and vector search technologies
• Experience with cloud platforms such as AWS, Google Cloud Platform including services like Vertex AI, BigQuery or SageMaker
• Experience working in startup or high-growth environments
• Proven ability to lead-cross-functional teams and deliver results in a multicultural, global organization
• Hands-on experience with modern ML frameworks such as TensorFlow, PyTorch, Scikit[1]learn, Keras, XGBoost, LightGMB, and H2o.ai
• Experience with ML lifecycle tools such as MLflow, Kubeflow, Weights & Biases, or Amazon SageMaker
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders
• Demonstrated ability to work independently and manage ambiguity in fast-paced environments

General Description of All Benefits

• Annual bonus is 0-20% of the base salary
• Medical/Dental/Vision/Life, AD&D insurance
• Flexible Spending Accounts (FSA) & Health Savings Account (HSA)
• Long-term/Short-term Disability
• Employee Assistance Program (EAP) program
• 401K Plan with Company Match
• 18-21 days of the Paid Time Off (PTO) a year based on the tenure
• 12 Public Holidays
• 6 weeks Paid Parental leave
• Pre-tax commuter benefits
• MTV - [Free] Electric Car Charging Station

General Description of Other Compensation

“Other Compensation” includes, but is not limited to, bonuses, equity, or other forms of compensation that would be offered to the hired applicant in addition to their established salary range or wage scale.

Coupang is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race (including traits historically associated with race, including but not limited to hair texture and protective hair styles), color, religion, religious creed (including religious dress and grooming practices), sex or gender (including pregnancy, childbirth, breastfeeding, and medical conditions related to pregnancy, childbirth or breastfeeding), gender identity, gender expression, sexual orientation, ,ancestry, national origin (including language use restrictions), age (40 and over), physical or mental disability, medical condition, genetic information, HIV/AIDS or Hepatitis C status, family status (including but not limited to marital or domestic partnership status), military or veteran status, use of a trained dog guide or service animal, political activities or affiliations, ancestry, citizenship, family and medical leave status, status as a victim of any violent crime, or any other characteristic or class protected by the laws or regulations in the locations where we operate.

Recruitment Process and Others

Recruitment Process

• Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer

• The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances.

• Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage.

Details to Consider

• This job posting may be closed prior to the stated end date for application if all openings are filled.

• Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process.

• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.

Privacy Notice Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below: https://www.coupang.jobs/privacy-policy/

If you need assistance and/or a reasonable accommodation in the application of recruiting process due to a disability, please contact us at usrecruiting@coupang.com.

Requisition ID: R0072711

Please complete the attached Internal Transfer Request Form and submit.  

Please make sure to apply with your Coupang e-mail address.  

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.

Role Overview

As our Staff Machine Learning Engineer for Coupang Media Group, Ads Quality, you will be responsible for developing, designing machine learning models, optimization algorithms and new product features for our advertising platform. 

The Coupang Media Group (CMG) is responsible for providing vendors that sell their products on Coupang a host of marketing products and services.  We launched Product Ads performance advertising marketplace late in 2018.  We have grown rapidly to over 10,000 active advertisers and 150M daily ad impressions in only 5 months’ time. Our group is responsible for advertising brands and products inside our e-commerce website. To get an idea of how valuable that is, both Alibaba and Amazon make more money on advertising than on selling products.  

This is an opportunity to be part of building up a new development organization with strong revenue potential inside a successful company. We’re building full-stack engineering teams to handle large scale advertising problems, including real-time behavioral targeting, auctioning and bidding systems and search based advertising. 

We are in the growth phase of the organization, so you’ll be a part of managing the transition from growth phase to enterprise processes. 

In this role you will be responsible for innovating and building our new ad quality stack for our ads platform  and eventually extend it into a full ad exchange, DSP, and SSP. We currently handle about 1bn impressions per day from internal traffic alone. 

What You Will do

• Design features and build large-scale machine learning models and systems to improve ad targeting, relevance, ranking, and engagement 
• Design and implement large-scale ML systems for search ranking, semantic retrieval, query understanding, and personalized product discovery using state-of-the-art techniques such as transformer-based models, contrastive learning, and vector search
• Drive innovation in search relevance and user intent modeling using large language models (LLMs), embedding-based retrieval, and multi-modal learning
• Build and optimize ML pipelines using tools such as Apache Spark, Airflow, Kubeflow, and MLflow, ensuring reproducibility, scalability, and operational excellence
• Define and track key performance metrics to evaluate model impact and identify high[1]leverage opportunities for improvement
• Collaborate cross-functionally with product, engineering, and data science teams to align technical solutions with business goals and customer experience
• Mentor and grow engineering talent, fostering a culture of technical excellence, experimentation and continuous learning

Basic Qualifications

• Bachelor's degree in computer science, electrical engineering, mathematics, statistics or closely related fields
• 4 years of professional experience in applied machine learning
• Experience in machine learning, deep learning, and statistical modeling
• Proficiency in Python and/or Java, with experience in building production grade ML systems

Preferred Qualifications

• Master’s or PhD in relevant technical fields
• Experience with search systems, information retrieval or recommendation engines
• Experience with LLMs, embeddings, and vector search technologies
• Experience with cloud platforms such as AWS, Google Cloud Platform including services like Vertex AI, BigQuery or SageMaker
• Experience working in startup or high-growth environments
• Proven ability to lead-cross-functional teams and deliver results in a multicultural, global organization
• Hands-on experience with modern ML frameworks such as TensorFlow, PyTorch, Scikit[1]learn, Keras, XGBoost, LightGMB, and H2o.ai
• Experience with ML lifecycle tools such as MLflow, Kubeflow, Weights & Biases, or Amazon SageMaker
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders
• Demonstrated ability to work independently and manage ambiguity in fast-paced environments

Pay & Benefits

Our compensation reflects the cost of living across several US geographic markets. At Coupang, your base pay is one part of your total compensation.

The base pay for Staff position ranges from $152K/year to $261K/year. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.

General Description of All Benefits

• Annual bonus is 0-20% of the base salary
• Medical/Dental/Vision/Life, AD&D insurance
• Flexible Spending Accounts (FSA) & Health Savings Account (HSA)
• Long-term/Short-term Disability
• Employee Assistance Program (EAP) program
• 401K Plan with Company Match
• 18-21 days of the Paid Time Off (PTO) a year based on the tenure
• 12 Public Holidays
• 6 weeks Paid Parental leave
• Pre-tax commuter benefits
• MTV - [Free] Electric Car Charging Station

General Description of Other Compensation

“Other Compensation” includes, but is not limited to, bonuses, equity, or other forms of compensation that would be offered to the hired applicant in addition to their established salary range or wage scale.

Coupang is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race (including traits historically associated with race, including but not limited to hair texture and protective hair styles), color, religion, religious creed (including religious dress and grooming practices), sex or gender (including pregnancy, childbirth, breastfeeding, and medical conditions related to pregnancy, childbirth or breastfeeding), gender identity, gender expression, sexual orientation, ,ancestry, national origin (including language use restrictions), age (40 and over), physical or mental disability, medical condition, genetic information, HIV/AIDS or Hepatitis C status, family status (including but not limited to marital or domestic partnership status), military or veteran status, use of a trained dog guide or service animal, political activities or affiliations, ancestry, citizenship, family and medical leave status, status as a victim of any violent crime, or any other characteristic or class protected by the laws or regulations in the locations where we operate.

Recruitment Process and Others

Recruitment Process

• Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer

• The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances.

• Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage.

Details to Consider

• This job posting may be closed prior to the stated end date for application if all openings are filled.

• Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process.

• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.

Privacy Notice Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below: https://www.coupang.jobs/privacy-policy/

If you need assistance and/or a reasonable accommodation in the application of recruiting process due to a disability, please contact us at usrecruiting@coupang.com.

Requisition ID: R0072711

Please complete the attached Internal Transfer Request Form and submit.  

Please make sure to apply with your Coupang e-mail address.  

• Proactively drive the execution of end-to-end data platform, data quality roadmap for Search & Discovery ML efforts
• Take ownership, consolidate and optimize the Search & Discovery core data logging, processing, and ML model training pipelines
• Develop and scale data infrastructure that powers batch and real-time data processing, monitoring, and debugging for ML experiments
• Drive design and implementation of scalable ML based ranking system and online ML inference services
• Build strong cross-functional partnerships with Data Scientists, Analysts, Product Managers, Indexing Platform Engineers, Ranking Engineers and Data Platform Engineers to understand both the offline and online needs and deliver on those needs
• Research, analyze and select technical approaches for solving difficult and challenging development and integration problems, coach and mentor other engineers in process and methodologies

Basic Qualifications

• Bachelor's degree in computer science, electrical engineering, mathematics, statistics or
  closely related fields
• 8 years of professional experience in applied machine learning
• Experience in machine learning, deep learning, and statistical modeling
• Proficiency in Python and/or Java, with experience in building production grade ML
  systems

Preferred Qualifications

• Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning)
• Experience with Big Data tools and ETL frameworks (Hadoop, Hive, Presto, Spark, Scala, Apache Airflow, etc.)
• Experience with ML frameworks such as Tensorflow and Pytorch
• Experience with deploying highly robust and scalable data pipelines processing petabytes of data
• Experience in managing mission critical services with high throughput and low latency
• Experience with integrating applications and platforms with cloud technologies (i.e, AWS and GCP)
• Strong verbal and written communication skills
• Ability to conduct meetings and make professional presentations, and explain complex concepts and technical material to non-technical users
• Experience with machine learning platform for search & discovery related rankings is a strong plus

Pay & Benefits

Our compensation reflects the cost of living across several US geographic markets. At Coupang, your base pay is one part of your total compensation.

The base pay for this position ranges from $174,000K/year to $299,000K/year. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.

General Description of All Benefits

• Medical/Dental/Vision/Life, AD&D insurance
• Flexible Spending Accounts (FSA) & Health Savings Account (HSA)
• Long-term/Short-term Disability
• Employee Assistance Program (EAP) program
• 401K Plan with Company Match
• 18-21 days of the Paid Time Off (PTO) a year based on the tenure
• 12 Public Holidays
• Paid Parental leave
• Pre-tax commuter benefits
• MTV - [Free] Electric Car Charging Station

General Description of Other Compensation

"Other Compensation" includes, but is not limited to, bonuses, equity, or other forms of compensation that would be offered to the hired applicant in addition to their established salary range or wage scale.

• Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer
• The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances.
• Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage

Details to Consider

• This job posting may be closed prior to the stated end date for application if all openings are filled.
• Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process.
• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.

Privacy Notice

• Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below: https://www.coupang.jobs/privacy-policy/

Coupang is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race (including traits historically associated with race, including but not limited to hair texture and protective hair styles), color, religion, religious creed (including religious dress and grooming practices), sex or gender (including pregnancy, childbirth, breastfeeding, and medical conditions related to pregnancy, childbirth or breastfeeding), gender identity, gender expression, sexual orientation, ,ancestry, national origin (including language use restrictions), age (40 and over), physical or mental disability, medical condition, genetic information, HIV/AIDS or Hepatitis C status, family status (including but not limited to marital or domestic partnership status), military or veteran status, use of a trained dog guide or service animal, political activities or affiliations, ancestry, citizenship, family and medical leave status, status as a victim of any violent crime, or any other characteristic or class protected by the laws or regulations in the locations where we operate. Coupang is also committed to providing a safe work environment for its employees and its consumers.

If you need assistance and/or a reasonable accommodation in the application of recruiting process due to a disability, please contact us at usrecruiting@coupang.com.

Job Requisition ID: R0069890

Please complete the attached Internal Transfer Request Form and submit.  

Please make sure to apply with your Coupang e-mail address.  

• Proactively drive the execution of end-to-end data platform, data quality roadmap for Search & Discovery ML efforts
• Take ownership, consolidate and optimize the Search & Discovery core data logging, processing, and ML model training pipelines
• Develop and scale data infrastructure that powers batch and real-time data processing, monitoring, and debugging for ML experiments
• Drive design and implementation of scalable ML based ranking system and online ML inference services
• Build strong cross-functional partnerships with Data Scientists, Analysts, Product Managers, Indexing Platform Engineers, Ranking Engineers and Data Platform Engineers to understand both the offline and online needs and deliver on those needs
• Research, analyze and select technical approaches for solving difficult and challenging development and integration problems, coach and mentor other engineers in process and methodologies

Basic Qualifications

• Bachelor's degree in computer science, electrical engineering, mathematics, statistics or 
  closely related fields
• 8 years of professional experience in applied machine learning
• Experience in machine learning, deep learning, and statistical modeling
• Proficiency in Python and/or Java, with experience in building production grade ML 
  systems

Preferred Qualifications

• Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning)
• Experience with Big Data tools and ETL frameworks (Hadoop, Hive, Presto, Spark, Scala, Apache Airflow, etc.)
• Experience with ML frameworks such as Tensorflow and Pytorch
• Experience with deploying highly robust and scalable data pipelines processing petabytes of data
• Experience in managing mission critical services with high throughput and low latency
• Experience with integrating applications and platforms with cloud technologies (i.e, AWS and GCP)
• Strong verbal and written communication skills
• Ability to conduct meetings and make professional presentations, and explain complex concepts and technical material to non-technical users
• Experience with machine learning platform for search & discovery related rankings is a strong plus

Pay & Benefits

Our compensation reflects the cost of living across several US geographic markets. At Coupang, your base pay is one part of your total compensation.

The base pay for this position ranges from $174,000K/year to $299,000K/year. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.

General Description of All Benefits

• Medical/Dental/Vision/Life, AD&D insurance
• Flexible Spending Accounts (FSA) & Health Savings Account (HSA)
• Long-term/Short-term Disability
• Employee Assistance Program (EAP) program
• 401K Plan with Company Match
• 18-21 days of the Paid Time Off (PTO) a year based on the tenure
• 12 Public Holidays
• Paid Parental leave
• Pre-tax commuter benefits
• MTV - [Free] Electric Car Charging Station

General Description of Other Compensation

"Other Compensation" includes, but is not limited to, bonuses, equity, or other forms of compensation that would be offered to the hired applicant in addition to their established salary range or wage scale. 

• Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer
• The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances.
• Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage

Details to Consider

• This job posting may be closed prior to the stated end date for application if all openings are filled.
• Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process.
• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.

Privacy Notice

• Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below: https://www.coupang.jobs/privacy-policy/

Coupang is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race (including traits historically associated with race, including but not limited to hair texture and protective hair styles), color, religion, religious creed (including religious dress and grooming practices), sex or gender (including pregnancy, childbirth, breastfeeding, and medical conditions related to pregnancy, childbirth or breastfeeding), gender identity, gender expression, sexual orientation, ,ancestry, national origin (including language use restrictions), age (40 and over), physical or mental disability, medical condition, genetic information, HIV/AIDS or Hepatitis C status, family status (including but not limited to marital or domestic partnership status), military or veteran status, use of a trained dog guide or service animal, political activities or affiliations, ancestry, citizenship, family and medical leave status, status as a victim of any violent crime, or any other characteristic or class protected by the laws or regulations in the locations where we operate. Coupang is also committed to providing a safe work environment for its employees and its consumers.

If you need assistance and/or a reasonable accommodation in the application of recruiting process due to a disability, please contact us at usrecruiting@coupang.com.

Job Requisition ID: R0069890

About the Team 

The DMP team plays a critical role in Roku’s Advertising organization, leading initiatives around audience management that power decision-making across the advertising ecosystem. We develop and manage products that enable advanced segmentation and audience management for advertisers while meeting the operational needs of internal teams. 

We work closely with Product Managers, Machine Learning, Ad Sales, Ads Operations, and multiple groups within Advertising Engineering to deliver high-impact solutions.  

Looking ahead, we are exploring AI-driven capabilities to further enhance the effectiveness of advertising campaigns and improve operational efficiency of our platforms. 

About the Role 

We are seeking a highly skilled Senior Software Engineer with deep expertise in big data technologies, including Apache Spark and Apache Airflow. This hybrid position bridges software engineering and data engineering, requiring the ability to design, build, and maintain scalable systems for both application development and large-scale data processing. 

In this role, you will collaborate with cross-functional teams to architect and manage robust, production-grade data products and APIs that power critical capabilities across the advertising platform. You will work with technologies such as Apache Spark, Apache Airflow, ScyllaDB/Cassandra, Aerospike, Kubernetes, and SpringBoot to deliver reliable, high-performance solutions. 

The ideal candidate is a proactive, self-motivated professional with a strong track record in building high-scale data services and a dedication to delivering exceptional results. 

What You’ll Be Doing 

Software Development 

• Design and build APIs and backend services using Spring Boot to support data products and audience management workflows. 

• Write clean, maintainable, and efficient code, ensuring adherence to best practices through code reviews. 

Big Data Engineering 

• Design, develop, and maintain data pipelines and ETL workflows using Apache Spark and Apache Airflow. 

• Optimize data storage, retrieval, and processing systems to ensure reliability, scalability, and performance. 

• Develop and fine-tune complex queries using Apache Spark for large-scale datasets. 

• Monitor, troubleshoot, and improve data systems to minimize downtime and maximize efficiency. 

API and Platform Development

• Design, Development, and maintain large scale, low latency API systems using SpringBoot and Kubernetes

• Maintain NoSQL Infrastructure including ScyllaDB and Aerospike

Collaboration & Mentorship 

• Partner with the machine learning team, software engineers, and other teams to deliver integrated, high-quality solutions. 

• Provide technical guidance and mentorship to junior engineers, promoting best practices in software and data engineering. 

We’re Excited If You Have 

• 8+ years of experience in software and/or data engineering with expertise in big data technologies such as Apache Spark, Apache Airflow. 

• Expertise with at least one of the following ScyllaDB and Aerospike (preferred). 

• Strong understanding of SOLID principles and distributed systems architecture. 

• Proven experience in distributed data processing, data warehousing, and real-time data pipelines. 

• Advanced SQL skills, with expertise in query optimization for large datasets. 

• Exceptional problem-solving abilities and the capacity to work independently or collaboratively. 

• Excellent verbal and written communication skills. 

• Experience with cloud platforms such as AWS, GCP, or Azure, and containerization tools like Docker and Kubernetes. (preferred) 

• Experience in AdTech, in advertising data platforms and audience management. (preferred)

• Strong programming skills in Python, Java, and/or Scala. (preferred) 

• Knowledge of CI/CD pipelines, DevOps practices, and infrastructure-as-code tools (e.g., Jenkins & Terraform). (preferred) 

• Expertise in data modeling, schema design, and data visualization tools. Experience with building Agentic AI systems to automate decision-making and enhance analytics workflows. (preferred) 

• Bachelor's degree in computer science, Engineering, or a related field (or equivalent experience). 

#LI-GL1

About the Team 

The DMP team plays a critical role in Roku’s Advertising organization, leading initiatives around audience management that power decision-making across the advertising ecosystem. We develop and manage products that enable advanced segmentation and audience management for advertisers while meeting the operational needs of internal teams. 

We work closely with Product Managers, Machine Learning, Ad Sales, Ads Operations, and multiple groups within Advertising Engineering to deliver high-impact solutions.  

Looking ahead, we are exploring AI-driven capabilities to further enhance the effectiveness of advertising campaigns and improve operational efficiency of our platforms. 

About the Role 

We are seeking a highly skilled Senior Software Engineer with deep expertise in big data technologies, including Apache Spark and Apache Airflow. This hybrid position bridges software engineering and data engineering, requiring the ability to design, build, and maintain scalable systems for both application development and large-scale data processing. 

In this role, you will collaborate with cross-functional teams to architect and manage robust, production-grade data products and APIs that power critical capabilities across the advertising platform. You will work with technologies such as Apache Spark, Apache Airflow, ScyllaDB/Cassandra, Aerospike, Kubernetes, and SpringBoot to deliver reliable, high-performance solutions. 

The ideal candidate is a proactive, self-motivated professional with a strong track record in building high-scale data services and a dedication to delivering exceptional results. 

What You’ll Be Doing 

Software Development 

• Design and build APIs and backend services using Spring Boot to support data products and audience management workflows. 

• Write clean, maintainable, and efficient code, ensuring adherence to best practices through code reviews. 

Big Data Engineering 

• Design, develop, and maintain data pipelines and ETL workflows using Apache Spark and Apache Airflow. 

• Optimize data storage, retrieval, and processing systems to ensure reliability, scalability, and performance. 

• Develop and fine-tune complex queries using Apache Spark for large-scale datasets. 

• Monitor, troubleshoot, and improve data systems to minimize downtime and maximize efficiency. 

API and Platform Development

• Design, Development, and maintain large scale, low latency API systems using SpringBoot and Kubernetes

• Maintain NoSQL Infrastructure including ScyllaDB and Aerospike

Collaboration & Mentorship 

• Partner with the machine learning team, software engineers, and other teams to deliver integrated, high-quality solutions. 

• Provide technical guidance and mentorship to junior engineers, promoting best practices in software and data engineering. 

We’re Excited If You Have 

• 8+ years of experience in software and/or data engineering with expertise in big data technologies such as Apache Spark, Apache Airflow. 

• Expertise with at least one of the following ScyllaDB and Aerospike (preferred). 

• Strong understanding of SOLID principles and distributed systems architecture. 

• Proven experience in distributed data processing, data warehousing, and real-time data pipelines. 

• Advanced SQL skills, with expertise in query optimization for large datasets. 

• Exceptional problem-solving abilities and the capacity to work independently or collaboratively. 

• Excellent verbal and written communication skills. 

• Experience with cloud platforms such as AWS, GCP, or Azure, and containerization tools like Docker and Kubernetes. (preferred) 

• Experience in AdTech, in advertising data platforms and audience management. (preferred)

• Strong programming skills in Python, Java, and/or Scala. (preferred) 

• Knowledge of CI/CD pipelines, DevOps practices, and infrastructure-as-code tools (e.g., Jenkins & Terraform). (preferred) 

• Expertise in data modeling, schema design, and data visualization tools. Experience with building Agentic AI systems to automate decision-making and enhance analytics workflows. (preferred) 

• Bachelor's degree in computer science, Engineering, or a related field (or equivalent experience). 

#LI-GL1

About the Team 

The Ads Analytics team plays a critical role in Roku’s Advertising organization, leading measurement and analytics initiatives that power decision-making across the advertising ecosystem. We develop and manage products that deliver actionable insights for advertisers while meeting the operational and analytical needs of internal business teams. 

We work closely with Product Managers, Ad Sales, Ad Operations, Data Science, and multiple other software teams within the Advertising Engineering organization to deliver high-impact solutions.  

Looking ahead, we are exploring AI-driven measurement capabilities to further enhance the effectiveness of advertising campaigns and strengthen internal analytics. 

About the Role 

We are seeking a high skilled Senior Software Engineer with deep expertise in API Development using Spring Boot while also possessing knowledge of Apache Spark-based Big Data pipelines using Airflow. This hybrid position bridges software engineering and data engineering, requiring the ability to design, build, and maintain scalable systems for both application development and large-scale data processing. 

You will communicate and collaborate heavily with both business and engineering to ensure high quality standards and overall project delivery success. In this role, you will collaborate with cross-functional teams to architect and manage robust, production-grade data products that power critical analytics and measurement capabilities. You will work with technologies such as Apache Spark, Apache Airflow, Trino, Druid, Spring Boot, StarRocks, and Looker to deliver reliable, high-performance solutions. 

The ideal candidate is a proactive, self-motivated professional with a strong track record in building applications and services with a dedication to delivering exceptional results. 

What You’ll Be Doing 

Software Development 

• Design and build APIs and backend services using Spring Boot to support data products and analytics workflows. 

• Write clean, maintainable, and efficient code and tests, ensuring adherence to best practices through code reviews. 

Big Data Engineering 

• Design, develop, and maintain data pipelines and ETL workflows using Apache Spark and Apache Airflow. 

• Optimize data storage, retrieval, and processing systems to ensure reliability, scalability, and performance. 

• Develop and fine-tune complex queries and analytics solutions using Druid, Trino, and StarRocks for large-scale datasets. 

• Monitor, troubleshoot, and improve data systems to minimize downtime and maximize efficiency. 

Collaboration & Mentorship 

• Partner with data scientists, software engineers, and other teams to deliver integrated, high-quality solutions. 

• Provide technical guidance and mentorship to junior engineers, promoting best practices in software and data engineering. 

We’re Excited If You Have 

• 8+ years of experience in software and/or data engineering with expertise in big data technologies such as Apache Spark, Apache Airflow. 

• Expertise with at least one of the following: Apache Druid, StarRocks, and Trino. 

• Strong understanding of SOLID principles and distributed systems architecture. 

• Proven experience in distributed data processing, data warehousing, and real-time data pipelines. 

• Strong programming skills in Java, Python, or Scala.

• Advanced SQL skills, with expertise in query optimization for large datasets. 

• Expertise in data modeling, schema design, and data visualization tools.

• Experience building highly scalable, low-latency, APIs.

• Exceptional problem-solving abilities and the capacity to work both independently and collaboratively as needed. 

• Exceptional verbal and written communication skills. 

• Experience with cloud platforms such as AWS, GCP, or Azure, and containerization tools like Docker and Kubernetes. (preferred) 

• Experience in AdTech, in advertising data platforms and campaign measurement. (preferred)

• Knowledge of CI/CD pipelines, DevOps practices, and infrastructure-as-code tools (e.g., Terraform). (preferred) 

• Experience with building Agentic AI systems to automate decision-making and enhance analytics workflows. (preferred)  

• Bachelor's degree in computer science, Engineering, or a related field (or equivalent experience). 

About the Team 

The Ads Analytics team plays a critical role in Roku’s Advertising organization, leading measurement and analytics initiatives that power decision-making across the advertising ecosystem. We develop and manage products that deliver actionable insights for advertisers while meeting the operational and analytical needs of internal business teams. 

We work closely with Product Managers, Ad Sales, Ad Operations, Data Science, and multiple other software teams within the Advertising Engineering organization to deliver high-impact solutions.  

Looking ahead, we are exploring AI-driven measurement capabilities to further enhance the effectiveness of advertising campaigns and strengthen internal analytics. 

About the Role 

We are seeking a high skilled Senior Software Engineer with deep expertise in API Development using Spring Boot while also possessing knowledge of Apache Spark-based Big Data pipelines using Airflow. This hybrid position bridges software engineering and data engineering, requiring the ability to design, build, and maintain scalable systems for both application development and large-scale data processing. 

You will communicate and collaborate heavily with both business and engineering to ensure high quality standards and overall project delivery success. In this role, you will collaborate with cross-functional teams to architect and manage robust, production-grade data products that power critical analytics and measurement capabilities. You will work with technologies such as Apache Spark, Apache Airflow, Trino, Druid, Spring Boot, StarRocks, and Looker to deliver reliable, high-performance solutions. 

The ideal candidate is a proactive, self-motivated professional with a strong track record in building applications and services with a dedication to delivering exceptional results. 

What You’ll Be Doing 

Software Development 

• Design and build APIs and backend services using Spring Boot to support data products and analytics workflows. 

• Write clean, maintainable, and efficient code and tests, ensuring adherence to best practices through code reviews. 

Big Data Engineering 

• Design, develop, and maintain data pipelines and ETL workflows using Apache Spark and Apache Airflow. 

• Optimize data storage, retrieval, and processing systems to ensure reliability, scalability, and performance. 

• Develop and fine-tune complex queries and analytics solutions using Druid, Trino, and StarRocks for large-scale datasets. 

• Monitor, troubleshoot, and improve data systems to minimize downtime and maximize efficiency. 

Collaboration & Mentorship 

• Partner with data scientists, software engineers, and other teams to deliver integrated, high-quality solutions. 

• Provide technical guidance and mentorship to junior engineers, promoting best practices in software and data engineering. 

We’re Excited If You Have 

• 8+ years of experience in software and/or data engineering with expertise in big data technologies such as Apache Spark, Apache Airflow. 

• Expertise with at least one of the following: Apache Druid, StarRocks, and Trino. 

• Strong understanding of SOLID principles and distributed systems architecture. 

• Proven experience in distributed data processing, data warehousing, and real-time data pipelines. 

• Strong programming skills in Java, Python, or Scala.

• Advanced SQL skills, with expertise in query optimization for large datasets. 

• Expertise in data modeling, schema design, and data visualization tools.

• Experience building highly scalable, low-latency, APIs.

• Exceptional problem-solving abilities and the capacity to work both independently and collaboratively as needed. 

• Exceptional verbal and written communication skills. 

• Experience with cloud platforms such as AWS, GCP, or Azure, and containerization tools like Docker and Kubernetes. (preferred) 

• Experience in AdTech, in advertising data platforms and campaign measurement. (preferred)

• Knowledge of CI/CD pipelines, DevOps practices, and infrastructure-as-code tools (e.g., Terraform). (preferred) 

• Experience with building Agentic AI systems to automate decision-making and enhance analytics workflows. (preferred)  

• Bachelor's degree in computer science, Engineering, or a related field (or equivalent experience). 

About the Team

The Recommendations team drives personalized experiences across our platform by leveraging state-of-the-art machine learning. Our mission is to deliver meaningful, context-aware recommendations that adapt to each user's preferences in real time. We believe that true innovation in personalization requires more than great models—it depends on a robust, flexible ML platform built for experimentation and scale. To that end, we design and build the underlying ML infrastructure, ensuring our systems remain fast, reliable, and at the forefront of technology. Our work blends innovation, engineering excellence, and a deep commitment to understanding our users, shaping how they discover and engage with content every day.

About the Role

We seek an outstanding, creative, and passionate Machine Learning Platform Engineer to join Roku's Recommendation team. In this role, you will design, build, and scale robust distributed systems that power the next generation of personalized content recommendations for millions of Roku users. You will focus on developing end-to-end machine learning platforms and infrastructure, ensuring seamless deployment, monitoring, and optimization of algorithms and operational workflows that deliver unique experiences at scale.

For California Only - The estimated annual salary for this position is between $229,500 - $367,100 annually. Compensation packages are based on factors unique to each candidate, including but not limited to skill set, certifications, and specific geographical location. This role is eligible for health insurance, equity awards, life insurance, disability benefits, parental leave, wellness benefits, and paid time off.
    

What You'll Be Doing

• Design, build, and maintain scalable platform services: feature store, real-time inference services, vector DBs etc., that serve millions of transactions per second
• Run and monitor online AB tests via robust platform services, analyzing platform metrics and business KPIs to optimize recommendation system performance
• Collaborate closely with US-based engineering and cross-functional teams to translate business requirements into modular platform components and APIs
• Enhance and evolve the ML platform ecosystem to support high developer velocity, system scalability, and adaptability to future business needs
• Contribute to onboarding, training, and mentoring new team members on emerging platform engineering best practices and technologies
  
  

We’re Excited If You Have

• 5+ years of experience building software solutions to concrete problems
• Strong CS fundamentals. Should be able to write an algorithm with ease
• You are fluent with one of high-level programming languages like Java, Scala, Kotlin or Python
• We’d love to see that you’ve worked with big data systems (Spark, Kafka, Flink, S3, AirFlow)
• Familiar with model ML framework and tools: Ray, PyTorch, HuggingFace, AWS Sagemaker
• AI literacy and curiosity. You have either tried Gen AI in your previous work or outside of work or are curious about Gen AI and have explored it.
• MS in Computer Science or related field

#LI-SSC

About the Team

Roku pioneered TV streaming and continues to innovate and lead the industry. Continued success relies on investing in the Roku Content Platform, so we deliver high quality streaming TV experience at a global scale. As part of our Content Platform team you join a small group of highly skilled engineers, that own significant responsibility in crafting, developing and maintaining our large-scale backend systems, data pipelines, storage, and processing services. We provide all insights in regard to all content on Roku Devices. 

About the Role

We are looking for a Senior Software Engineer with vast experience in backend development, Data Engineering and Data Analytics to focus on building next level content platform and data intelligence, which empowers Search, Recommendation, and many more critical systems across Roku Platform. This is an excellent role for a senior professional who enjoys a high level of visibility, thrives on having a critical business impact, able to make critical decisions and is excited to work on a core data platform component which is crucial for many streaming components at Roku.

What You’ll Be Doing

• Work closely with product management team, content data platform services, and other internal consumer teams to contribute extensively to our content data platform and underlying architecture.
• Build low-latency and optimized streaming and batch data pipelines to enable downstream services.
• Build and support our Micro-services based Event-Driven Backend Systems & Data Platform.
• Design and build data pipelines for batch, near-real-time, and real-time processing.
• Participate in architecture discussions, influence product roadmap, and take ownership and responsibility over new projects.

We’re excited if you have

• 8+ years professional experience as a Software Engineer.
• Proficiency in Java/Scala/Python.
• Deep understanding of backend technologies, architecture patterns, and best practices, including microservices, RESTful APIs, message queues, caching, and databases.
• Strong analytical and problem-solving skills, data structures and algorithms, with the ability to translate complex technical requirements into scalable and efficient solutions.
• Experience with Micro-service and event-driven architectures.
• Experience with Apache Spark and Apache Flink.
• Experience with Big Data Frameworks and Tools: MapReduce, Hive, Presto, HDFS, YARN, Kafka, etc.
• Experience with Apache Airflow or similar workflow orchestration tooling for ETL.
• Experience with cloud platforms: AWS (preferred), GCP, etc.
• Strong communication and presentation skills.
• BS in Computer Science; MS in Computer Science preferred.
• AI literacy and curiosity.You have either tried Gen AI in your previous work or outside of work or are curious about Gen AI and have explored it.

#LI-SJ1

About the team 

The Ads Analytics team plays a critical role in Roku’s Advertising organization, leading measurement and analytics initiatives that power decision-making across the advertising ecosystem. We develop and manage products that deliver actionable insights for advertisers while meeting the operational and analytical needs of internal business teams.  

We work closely with Product Managers, Ad Sales, Ad Operations, Data Science, and multiple other software teams within the Advertising Engineering organization to deliver high-impact solutions.   

Looking ahead, we are exploring AI-driven measurement capabilities to further enhance the effectiveness of advertising campaigns and strengthen internal analytics. 

About the role 

We are seeking a high skilled Senior Software Engineer with deep expertise in API Development using Spring Boot while also possessing knowledge of Apache Spark-based Big Data pipelines using Airflow. This hybrid position bridges software engineering and data engineering, requiring the ability to design, build, and maintain scalable systems for both application development and large-scale data processing.  

You will communicate and collaborate heavily with both business and engineering to ensure high quality standards and overall project delivery success. In this role, you will collaborate with cross-functional teams to architect and manage robust, production-grade data products that power critical analytics and measurement capabilities. You will work with technologies such as Apache Spark, Apache Airflow, Trino, Druid, Spring Boot, StarRocks, and Looker to deliver reliable, high-performance solutions.  

The ideal candidate is a proactive, self-motivated professional with a strong track record in building applications and services with a dedication to delivering exceptional results. 

What you’ll be doing  

Software Development  

• Design and build APIs and backend services using Spring Boot to support data products and analytics workflows.  
• Write clean, maintainable, and efficient code and tests, ensuring adherence to best practices through code reviews.  

Big Data Engineering  

• Design, develop, and maintain data pipelines and ETL workflows using Apache Spark and Apache Airflow.  
• Optimize data storage, retrieval, and processing systems to ensure reliability, scalability, and performance.  
• Develop and fine-tune complex queries and analytics solutions using Druid, Trino, and StarRocks for large-scale datasets.  
• Monitor, troubleshoot, and improve data systems to minimize downtime and maximize efficiency.  

Collaboration & Mentorship  

• Partner with data scientists, software engineers, and other teams to deliver integrated, high-quality solutions.  
• Provide technical guidance and mentorship to junior engineers, promoting best practices in software and data engineering. 

We’re excited if you have  

• 10+ years professional software development experience. 
• Experience building highly scalable, low-latency REST services and API frameworks. 
• Able to efficiently write SQL queries and analyze results to explore business problems and inquiries.
• Ability to translate queries and reporting requirements into production-level data processing pipelines.
• Proficient in day-to-day use of Python / Java / Scala.
• Strong understanding of and experience with distributed computing frameworks like Hive/Hadoop and Apache Spark.
• Expertise in data modeling, schema design, and data visualization tools. 
• Experience working in GCP and/or AWS is a plus.
• Experience with JavaScript, Node.js and React is nice to have.
• Experience deploying services on Kubernetes is a plus. 
• Knowledge of CI/CD pipelines, DevOps practices, and infrastructure-as-code tools (e.g., Terraform) is a plus. 
• Background in computer science or similar quantitative field. 

About the team

Roku runs one of the largest data lakes in the world. We store over 70 PB of data, run 10+M queries per month, scan over 100 PB of data per month. 
Big Data team is the one responsible for building, running, and supporting the platform that makes this possible. We provide all the tools needed to acquire, generate, process, monitor, validate and access the data in the lake for both streaming data and batch. We are also responsible for generating the foundational data. The systems we provide include Scribe, Kafka, Hive, Presto, Spark, Flink, Pinot, and others. The team is actively involved in the Open Source, and we are planning to increase our engagement over time. 

About the Role 

Roku is in the process of modernizing its Big Data Platform. We are working on defining the new architecture to improve user experience, minimize the cost and increase efficiency. Are you interested in helping us build this state-of-the-art big data platform? Are you an expert with Big Data Technologies? Have you looked under the hood of these systems? Are you interested in Open Source? If you answered “Yes” to these questions, this role is for you! 

What you will be doing 

• You will be responsible for streamlining and tuning existing Big Data systems and pipelines and building new ones. Making sure the systems run efficiently and with minimal cost is a top priority 
• You will be making changes to the underlying systems and if an opportunity arises, you can contribute your work back into the open source 
• You will also be responsible for supporting internal customers and on-call services for the systems we host. Making sure we provided stable environment and great user experience is another top priority for the team 

We are excited if you have 

• 10+ years of production experience building big data platforms based upon Spark, Trino or equivalent 
• Strong programming expertise in Java, Scala, Kotlin or another JVM language. 
• A robust grasp of distributed systems concepts, algorithms, and data structures 
• Strong familiarity with the Apache Hadoop ecosystem: Spark, Kafka, Hive/Iceberg/Delta Lake, Presto/Trino, Pinot, etc. 
• Experience working with at least 3 of the technologies/tools mentioned here: Big Data / Hadoop, Kafka, Spark, Trino, Flink, Airflow, Druid, Hive, Iceberg, Delta Lake, Pinot, Storm etc 
• Extensive hands-on experience with public cloud AWS or GCP 
• BS/MS degree in CS or equivalent
• AI Literacy /AI growth mindset

About the team

When you join our Core Analytics Team, you will be part of a centralized analytics team, with all the benefits that entail: a world class peer group to support you, centrally maintained tools, career growth, and more. 

This role will specifically support the Device/OS Analytics team, partnering closely with product, engineering, and analytics teams to drive data-informed decisions that enhance device performance, reliability, and user experience. 

About the role

Roku is looking for a Business Intelligence Engineer to play an instrumental role in helping Roku continue its success by providing end-to-end business intelligence solutions that democratize data across the business. You will work closely with analysts, data engineers, and business stakeholders to understand business questions, write robust pipelines to create analytical data assets, and use visualization to create informative reports and dashboards that allow stakeholders to answer questions quickly and with confidence. You will become an expert in our data infrastructure and create/maintain pipelines that are critical to conducting robust analyses. The ideal candidate for this role loves building tools and reports that empower others to make high impact decisions and tell stories with data. 

What you will be doing

• Work directly with analysts and engineers to understand goals, gather requirements, and guide development of new data assets by producing robust feature guides 
• Build and support robust data pipelines to support business tools and analytical needs and meet SLAs 
• Conduct UAT on new tables 
• Liaise with data engineers to understand and communicate the impacts of underlying changes in the data and update dependent pipelines 
• Identify and fill gaps among our data assets and key metrics 
• Serve as the resident expert in understanding the nuance of our data infrastructure for the analytics team. You will be the go-to-person when questions arise around the correct dataset, proper joins, bugs, etc. 
• Create reports, dashboards, visualizations, and self-service tools that help partners monitor business trends and key metrics 
• Monitor key metrics and business processes to identify trends and uncover root causes that drive business impact 

We're excited if you have

• 3+ years of relevant work experience in Analytics, Business Intelligence, or Technical Operations 
• Master in SQL, Python, and ETL using big data tools (HIVE/Presto, Spark) 
• Experience writing data pipelines using Airflow 
• Fluency in Looker and/or Tableau 
• Strong understanding of data warehousing principles, pipelines, and APIs 
• AI experience is a plus 
• Strong communication skills 
• The ability to work independently and across multiple time zones 
• Ownership mindset- you own the end-to-end lifecycle of a product starting from ideation to adoption and maintenance 
• Bachelors or Masters in math, physics, computer science, economics or equivalent 

#LI-AK1

About the Team

The Advanced Development team at Roku pushes beyond today’s product lines to invent the next generation of intelligent and generative media systems.
We explore ideas that sit years ahead of production, developing foundational technologies that will redefine how content is understood, created, and personalised across millions of Roku devices.

This is a rare environment — a PhD-level, cross-disciplinary group combining machine learning research, software engineering, and DevOps.
Everyone here is an expert, but not narrowly focused. The team blends deep technical mastery with broad creative vision — people who challenge convention, embrace ambiguity, and build what’s never been built before. It’s a collaborative, low-ego, ownership-driven culture built on trust and curiosity.

We’re seeking an Applied Scientist with a strong foundation in mathematics, machine learning, and computer science, combined with experience in cloud engineering, DevOps, and computer vision — someone who thrives where research meets production.

About the Role

As a Senior Applied Machine Learning Engineer, you’ll help design, build, and deploy the systems that make media smarter.
You’ll work across the full model and software lifecycle, from prototype to production, developing scalable ML pipelines and cloud architectures that power generative AI, intelligent media understanding, content analysis, and advertising intelligence.

You’ll operate at the intersection of machine learning, infrastructure, and software engineering, taking ownership from data collection through deployment — and seeing your work directly influence how audiences experience Roku’s content and advertising ecosystem.

What You’ll Be Doing

• Deploying scalable, fault-tolerant computer vision, media understanding, and generative AI systems to production

• Overseeing the full model development cycle: ideation, prototyping, implementation, deployment, testing, and operations

• Designing uncertainty metrics and communicating results to both technical and non-technical stakeholders

• Gathering and compiling datasets, defining annotation ontologies, auditing annotation operations, and ensuring data quality

• Staying up to date with industry and academic trends in computer vision, machine learning, and generative models for media and advertising

• Working closely with product and other engineering teams to implement new content and advertising experiences through cloud services

• Integrating services from other teams around the company, while also providing reusable ML services to others

• Evaluating and providing feedback on new platform technologies provided by internal teams

• Working with QA teams to address bugs and contribute to automation and quality assurance

We’re Excited If You Have

• A Master’s degree (PhD preferred) in Computer Science, Applied Mathematics, or a related field

• Strong background developing applied machine learning systems using PyTorch or TensorFlow

• Expertise in image processing, computer vision, or natural language processing

• Experience using AWS, GCP, or Azure for storing data, training, and serving models

• Proven ability to evaluate models and communicate insights effectively

• Experience building APIs with frameworks such as GraphQL or REST

• Experience with workflow orchestration tools such as Airflow, Argo, AWS Step Functions, or Metaflow

• Hands-on experience with Docker, Kubernetes, Terraform, CloudFormation, CI/CD automation, and Python build or packaging tools

#LI-PA1

Roku is the #1 TV streaming platform in the US, and we’ve set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers with unique capabilities to engage consumers.   

From your first day at Roku, you’ll make a valuable — and valued — contribution. We’re a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers worldwide while gaining meaningful experience across various disciplines. 

About the team 

Our team’s mission is to build cutting-edge advertising technology to support and help grow sustainable advertising business. The team owns server technologies, reporting infrastructure, data, cloud services, and test engineering for the advertising platforms within Roku. We also work closely with internal and external customers to help them achieve their advertising goals. 

About the role 

We are looking for an experienced manager to help grow the team, manage priorities, and communicate with stakeholders in an effective way. The role requires excellent communication skills in addition to a strong engineering background. The ideal candidate will have endless curiosity and can pair a global mindset with locally relevant execution. You should be a gritty problem solver and self-starter who can drive programs with the product and commercial teams within Roku and across external strategic partner organizations. The successful candidate will display a balance of hard and soft skills, including the ability to respond quickly to changing business needs. 
 

What you’ll be doing 

• Help grow the engineering team 

• Build scalable, resilient, and performant distributed systems for data processing, reporting and analytics 

• Work across engineering teams, data science, and product management to influence the direction of work and architecture 

• Communicate with internal stakeholders to inform and influence requirements and delivery  

• Take complete ownership of impactful initiatives and make pragmatic technical decisions. 

• Stakeholder management, developing good understanding of advertising business needs, building domain knowledge to understand systems and data better 

We’re excited if you have 
 

• 15+ years engineering experience working with modern big data technologies: Spark, Airflow, Scala, Java python, relational databases and related technologies 

• 6+ years’ experience leading technical teams and large-scale data processing systems 

• Experience building, growing and managing teams 

• Subject matter expertise in advertising and data processing 

• Solid understanding of data engineering, big data technologies, analytics and data science 

• Strong communication skills 

• Self-motivated individual with a high level of accountability and ownership 

• Critical thinker and practical decision maker 

• Can do, results-oriented mindset 

• Nonpolitical, collaborative, and team oriented 

About the role  

Our Search Platform sits at the heart of the Roku experience, powering voice, text, and visual discovery across 100M+ active accounts and every Roku-powered device worldwide.
 We own the entire stack —from ingesting & enriching a multi-million-title knowledge graph, to low-latency retrieval services and large-scale machine-learning systems that personalize results in real time. Our work doesn’t just help users find shows; it drives core product surfaces (home-screen rows, browse hubs, Roku Voice, mobile app search) and fuels partner monetization. If you enjoy turning cutting-edge research into products used billions of times a day, you’ll thrive here.

Roku’s footprint has more than quadrupled in the past five years, and user expectations have leaped just as fast—think LLM-based query understanding, vector-DB retrieval, on-device models, and multimodal search (voice, text, image). We’re now rebuilding our relevance stack for the next decade, blending classic IR with generative-AI techniques. You will be a technical leader spearheading that transformation. 

What you'll be doing 

• Apply state of the art ML on search using techniques in deep learning, bandits, transformers, LLMs, causal inference, and optimizations to make our users more delighted and engaged on the platform 
• Run online AB tests and analyze them against the critical business KPIs 
• Collaborate with US engineering teams as well as cross-functional teams to translate business requirements into technical specifications 
• Nurture our ML ecosystem to make it withstand scale, developer velocity and future business shifts 
• Provide technical leadership to drive technical and ML roadmap for search ranking and monetization 
• Help recruiting new engineers. Interview, train, and mentor new team members 
  
  We're excited if you have 
  
  
• 7+ years of experience (or PhD with 5 years of experience) applying Machine Learning to concrete problems at large-scale in domains like recommendation or search or ads 
• Strong CS fundamentals. Should be able covert ideas to code with ease 
• Good understanding of machine learning fundamentals like classification, deep neural nets, and sequence-based models. Familiarity with modern NLP stack and multi-modal representation learning is a plus 
• We'd love to see that you've worked with big data systems (Spark, S3, and Airflow) and can program (Java, Scala, or Python)  
• Good understanding of system architecture 
• Experience in big data technologies and streaming architecture, data pipelines, etc. 
• MS in Computer Science, Statistics, or related field, but a Ph.D. in CS or related fields is preferred 
  
• AI literacy and curiosity.You have either tried Gen AI in your previous work or outside of work or are curious about Gen AI and have explored it. 

#LI-AK1

About the Team 

The DMP team plays a critical role in Roku’s Advertising organization, leading initiatives around audience management that power decision-making across the advertising ecosystem. We develop and manage products that enable advanced segmentation and audience management for advertisers while meeting the operational needs of internal teams. We work closely with Product Managers, Machine Learning, Ad Sales, Ads Operations, and multiple groups within Advertising Engineering to deliver high-impact solutions.Looking ahead, we are exploring AI-driven capabilities to further enhance the effectiveness of advertising campaigns and improve operational efficiency of our platforms. 

About the Role 

We are seeking a highly skilled Senior Software Engineer with deep expertise in big data technologies, including Apache Spark and Apache Airflow. This hybrid position bridges software engineering and data engineering, requiring the ability to design, build, and maintain scalable systems for both application development and large-scale data processing.In this role, you will collaborate with cross-functional teams to architect and manage robust, production-grade data products and APIs that power critical capabilities across the advertising platform. You will work with technologies such as Apache Spark, Apache Airflow, ScyllaDB/Cassandra, Aerospike, Kubernetes, and SpringBoot to deliver reliable, high-performance solutions. The ideal candidate is a proactive, self-motivated professional with a strong track record in building high-scale data services and a dedication to delivering exceptional results. 

What You’ll Be Doing 

Software Development 

• Design and build APIs and backend services using Spring Boot to support data products and audience management workflows. 

• Write clean, maintainable, and efficient code, ensuring adherence to best practices through code reviews. 

Big Data Engineering 

• Design, develop, and maintain data pipelines and ETL workflows using Apache Spark and Apache Airflow. 

• Optimize data storage, retrieval, and processing systems to ensure reliability, scalability, and performance. 

• Develop and fine-tune complex queries using Apache Spark for large-scale datasets. 

• Monitor, troubleshoot, and improve data systems to minimize downtime and maximize efficiency. 

API and Platform Development

• Design, Development, and maintain large scale, low latency API systems using SpringBoot and Kubernetes

• Maintain NoSQL Infrastructure including ScyllaDB and Aerospike

Collaboration & Mentorship 

• Partner with the machine learning team, software engineers, and other teams to deliver integrated, high-quality solutions. 

• Provide technical guidance and mentorship to junior engineers, promoting best practices in software and data engineering.

We’re Excited If You Have 

• Bachelor's degree in computer science, Engineering, or a related field (or equivalent experience). 

• 8+ years of experience in software and/or data engineering with expertise in big data technologies such as Apache Spark, Apache Airflow.

• Expertise in developing low latency APIs
  

• Strong understanding of SOLID principles and distributed systems architecture. 

• Proven experience in distributed data processing, data warehousing, and real-time data pipelines. 

• Advanced SQL skills, with expertise in query optimization for large datasets. 

• Exceptional problem-solving abilities and the capacity to work independently or collaboratively. 

• Excellent verbal and written communication skills. 

• Experience with cloud platforms such as AWS, GCP, or Azure, and containerization tools like Docker and Kubernetes. (preferred) 

• Experience in AdTech, in advertising data platforms and audience management. (preferred)

• Strong programming skills in Python, Java, and/or Scala. (preferred) 

• Knowledge of CI/CD pipelines, DevOps practices, and infrastructure-as-code tools (e.g., Jenkins & Terraform). (preferred) 

• Expertise in developing low latency APIs

•  Experience with building Agentic AI systems to automate decision-making and enhance analytics workflows. (preferred)

• Experience in AdTech, in advertising data platforms and audience management. (preferred)
  

About the Team 

The Data Insights team plays a critical role in Roku’s Advertising organization, leading measurement and analytics initiatives that power decision-making across the advertising ecosystem. We develop and manage products that deliver actionable insights for advertisers while meeting the operational and analytical needs of internal teams.We work closely with Product Managers, Data Science, Ad Sales, Ads Operations, and multiple groups within Advertising Engineering to deliver high-impact solutions. Looking ahead, we are exploring AI-driven measurement capabilities to further enhance the effectiveness of advertising campaigns and strengthen internal analytics. 

About the Role 

We are seeking a highly skilled Senior Software Engineer with deep expertise in big data technologies, including Apache Spark and Apache Airflow. This hybrid position bridges software engineering and data engineering, requiring the ability to design, build, and maintain scalable systems for both application development and large-scale data processing.In this role, you will collaborate with cross-functional teams to architect and manage robust, production-grade data products that power critical analytics and measurement capabilities. You will work with technologies such as Apache Spark, Apache Airflow, Trino, Druid, Spring Boot, StarRocks, and Looker to deliver reliable, high-performance solutions.The ideal candidate is a proactive, self-motivated professional with a strong track record in building high-scale data services and a dedication to delivering exceptional results.

What You’ll Be Doing 

Software Development 

• Design and build APIs and backend services using Spring Boot to support data products and analytics workflows. 

• Write clean, maintainable, and efficient code, ensuring adherence to best practices through code reviews. 

Big Data Engineering 

• Design, develop, and maintain data pipelines and ETL workflows using Apache Spark and Apache Airflow. 

• Optimize data storage, retrieval, and processing systems to ensure reliability, scalability, and performance. 

• Develop and fine-tune complex queries and analytics solutions using Druid, Trino, and StarRocks for large-scale datasets. 

• Monitor, troubleshoot, and improve data systems to minimize downtime and maximize efficiency. 

Collaboration & Mentorship 

• Partner with data scientists, software engineers, and other teams to deliver integrated, high-quality solutions. 

• Provide technical guidance and mentorship to junior engineers, promoting best practices in software and data engineering. 

We’re Excited If You Have 

• Bachelor's degree in computer science, Engineering, or a related field (or equivalent experience). 

• 8+ years of experience in software and/or data engineering with expertise in big data technologies such as Apache Spark, Apache Airflow. 

• Expertise with atleast one of the following Apache Druid, StarRocks, and Trino. 

• Strong understanding of SOLID principles and distributed systems architecture. 

• Proven experience in distributed data processing, data warehousing, and real-time data pipelines. 

• Advanced SQL skills, with expertise in query optimization for large datasets. 

• Exceptional problem-solving abilities and the capacity to work independently or collaboratively. 

• Excellent verbal and written communication skills. 

• Experience with cloud platforms such as AWS, GCP, or Azure, and containerization tools like Docker and Kubernetes. (preferred) 

• Familiarity with additional big data technologies, including Hadoop and Kafka.  

• Experience in AdTech, in advertising data platforms and campaign measurement. (preferred)

• Strong programming skills in Python, Java, or Scala. (preferred) 

• Knowledge of CI/CD pipelines, DevOps practices, and infrastructure-as-code tools (e.g., Terraform). (preferred) 

• Expertise in data modeling, schema design, and data visualization tools.

• Experience with building Agentic AI systems to automate decision-making and enhance analytics workflows. (preferred) 

About the team

The mission of Roku's Data Engineering team is to develop a world-class big data platform so that internal and external customers can leverage data to grow their businesses. Data Engineering works closely with business partners and Engineering teams to collect metrics on existing and new initiatives that are critical to business success. As Senior Data Engineer working on Device metrics, you will design data models & develop scalable data pipelines to capturing different business metrics across different Roku Devices.

About the role

Roku pioneered streaming to the TV. We connect users to the streaming content they love, enable content publishers to build and monetise large audiences, and provide advertisers with unique capabilities to engage consumers. Roku streaming players and Roku TV™ models are available around the world through direct retail sales and licensing arrangements with TV brands and pay-TV operators.With tens of million players sold across many countries, thousands of streaming channels and billions of hours watched over the platform, building scalable, highly available, fault-tolerant, big data platform is critical for our success.This role is based in Bangalore, India and requires hybrid working, with 3 days in the office.

What you'll be doing

• Build highly scalable, available, fault-tolerant distributed data processing systems (batch and streaming systems) processing over 10s of terabytes of data ingested every day and petabyte-sized data warehouse
• Build quality data solutions and refine existing diverse datasets to simplified data models encouraging self-service
• Build data pipelines that optimise on data quality and are resilient to poor quality data sources
• Own the data mapping, business logic, transformations and data quality
• Low level systems debugging, performance measurement & optimization on large production clusters
• Participate in architecture discussions, influence product roadmap, and take ownership and responsibility over new projects
• Maintain and support existing platforms and evolve to newer technology stacks and architectures

We're excited if you have

• Extensive SQL Skills
• Proficiency in at least one scripting language, Python is required
• Experience in big data technologies like HDFS, YARN, Map-Reduce, Hive, Kafka, Spark, Airflow, Presto, etc.
• Proficiency in data modeling, including designing, implementing, and optimizing conceptual, logical, and physical data models to support scalable and efficient data architectures.
• Experience with AWS, GCP, Looker is a plus
• Collaborate with cross-functional teams such as developers, analysts, and operations to execute deliverables
• 8+ years professional experience as a data Engineer 
• BS in Computer Science; MS in Computer Science preferred
• AI Literacy / AI growth mindset

#LI-AL1

Who We Are

Babylist is the leading registry, e-commerce, and content platform for growing families. More than 9 million people shop with Babylist every year, making it the go-to destination for seamless purchasing, trusted guidance, and expert product recommendations for new parents and the people who love them. What began as a universal registry has grown into a full ecosystem for new parents, including the Babylist Shop, Babylist Health, and a flagship showroom in Los Angeles. Hundreds of brands in baby and beyond partner with Babylist to engage meaningfully with families during one of life’s most important transitions. With over $1 billion in annual GMV, and more than $500 million in 2024 revenue, Babylist is reshaping the $320 billion baby product industry. We’re helping parents feel confident, connected, and cared for at every step. As we build the generational brand in baby, our mission remains simple: to connect growing families with everything they need to thrive.To learn more, visit www.babylist.com.

Our Ways of Working

Babylist is remote-first with team members across the U.S. and Canada who move fast, think smart, and use AI as part of how they work every day — not as an experiment, as an expectation. We come together twice a year to build the relationships behind the work, and we hire people who are genuinely excited about what's possible and prove it through how they show up.

How We Build

Babylist is in the middle of a fundamental shift in how software gets made, and we are not tiptoeing into it. We are rebuilding our engineering culture around a simple belief: AI changes everything. How teams are structured, how decisions get made, how fast ideas become working software. Our engineers own problems end to end, working directly with product, design, and business partners with short feedback loops and real stakeholder access. We ship, learn, and iterate fast. When something is not working, we throw it out and start over — project failure and personal failure are not the same thing here. AI tools are as natural to our workflow as an IDE or version control. We are not exploring this, we are living it. Our engineers use AI to explore tradeoffs, pressure-test designs, and move from problem to solution in hours instead of days. They generate code with AI so they can stay focused on the decisions that actually require human judgment — not the routine ones. More velocity means more time for craft: better test coverage, stronger architecture, and deeper customer understanding. We hold ourselves to a higher quality bar because of AI, not in spite of it. We are building this playbook in real time, and we are looking for people who want to build it with us. If you have already changed how you work because of AI — or you are ready to — and you care more about shipping something great than following a prescribed process, we should talk.

Our Tech Stack 

• React, Native iOS and Android
• Ruby on Rails
• AWS, Terraform
• MySQL
• Sidekiq
• Redis
• Shopify

What the Role Is

As Babylist’s Senior Engineering Manager, Machine Learning & Discovery+Site Monetization, you’ll lead the team driving the next era of our machine learning and personalization efforts across the product. This is a hands-on leadership role for a manager who remains technically fluent while scaling people, systems, and impact. You’ll manage and grow a high-performing ML-focused pod spanning product recommendations, search, PLPs, and site monetization, with a clear mandate: maximize revenue and user value across surface areas through personalization.

You’ll guide the team on technical direction behind our homepage feed, “add next” experience, and other core personalization surfaces, while building the foundations for long-term ML excellence at Babylist.

Who You Are

• 3+ years of experience as a front-line manager delivering production-grade software or ML systems
• 5+ years of experience as an individual contributor in ML or Data Science, plus proven experience leading teams that build end-to-end machine learning systems, ideally in personalization, recommendations, or consumer-facing ML products
• Deep familiarity with the Python ML ecosystem (e.g., pandas, sklearn, xgboost, PyTorch) and comfortable reviewing designs, unblocking technical challenges, and setting high technical standards
• Experience supervising ML Engineers and/or Data Scientists; bonus points for experience managing Software Engineers
• Strong understanding of the full ML lifecycle, including data pipelines, workflow orchestration (e.g., Airflow), deployment, monitoring, and iteration in production
• Product-minded: passionate about technology, but primarily motivated by solving real user problems and driving business impact
• Experience working with large-scale, real-time or near-real-time data systems
• Comfortable owning and evolving the ML tech stack end-to-end, from data and modeling through production systems
• Background in consumer-facing products; experience in e-commerce, marketplaces, or complex user journeys is strongly preferred
• You're genuinely excited about what AI can do - not just as a concept, but as something you want to get your hands on. At Babylist, every team uses AI daily, and we're looking for people who lean in.

How You Will Make An Impact

• Build and lead the ML & personalization function: Hire, mentor, and support a multidisciplinary team (Machine Learning Engineers, Software Engineers, Product Manager, and occasional Designer), shaping the roadmap, standards, and culture for ML at Babylist
• Own high-impact ML initiatives: Deliver personalization systems that improve discovery, engagement, and monetization across key surfaces, directly impacting business outcomes
• Set technical and algorithmic direction: Define modeling approaches, data strategy, and system architecture in partnership with senior technical leaders, balancing experimentation with scalable execution
• Be hands-on when needed: Review ML/DS designs and code, build proof-of-concept models, and conduct your own data science research to de-risk ideas and accelerate progress
• Develop talent: Coach engineers on technical growth, career progression, and performance, combining strong technical standards with empowerment
• Drive cross-functional alignment: Partner closely with Product, Design, Analytics Engineering, and Data to translate ambiguous business problems into clear technical direction
• Understand the full funnel: Develop a deep understanding of Babylist’s user journeys, user feedback loops, and financial models — and how ML systems influence them end-to-end

About Compensation

We use a market-based approach to compensation. The starting salary range for this role is:

USD - $250,000 to $308,000
CAD - $230,000 to $288,000

Your starting salary will be based on your location, experience, and qualifications, with increases over time tied to performance, role growth, and internal pay equity.

Why You Will Love Working At Babylist

Our Culture

• We work with focus and intention, then step away to recharge
• We believe in exceptional management and invest in tools and opportunities to connect with colleagues
• We build products that positively impact millions of people's lives
• AI tools are as natural to how we work as your IDE or version control — we're not exploring this, we're living it.

Growth & Development

• Competitive pay and meaningful opportunities for career advancement
• We believe technology and data can solve hard problems
• We're committed to career progression and performance-based advancement

Compensation & Benefits

• Competitive salary with equity and bonus opportunities
• Company-paid medical, dental, and vision insurance
• Retirement savings plan with company matching and flexible spending accounts
• Generous paid parental leave and PTO
• Remote work stipend to set up your office
• Perks for physical, mental, and emotional health, parenting, childcare, and financial planning

Important Notices

Recorded Interviews Babylist uses an interview recording tool to record and transcribe interviews for evaluation purposes in accordance with applicable privacy laws. By participating in an interview, you consent to this recording and transcription.

Interview Integrity At Babylist, every team uses AI daily and we love it. During interviews though, we want to see you — your thinking, your problem-solving, your creativity. All interviews and assessments should be completed independently without AI tools or third-party assistance unless we tell you otherwise. We'll always be clear when AI is welcome. Misrepresentation during the process may result in removal from consideration.

Protect Yourself from Scams All official communication comes from the Babylist Talent Team via @babylist.com email addresses. We will never ask for payment, bank information, or personal financial details. If you receive outreach via WhatsApp, Telegram, or a non-Babylist email, it's not us. Verify open roles on our careers page.

Connections at Babylist In line with our conflict of interest policy, please let us know if you have a family member or close personal relationship with a current Babylist employee. This helps us keep our process fair for everyone.

Text Message Updates You may opt in to receive SMS updates about your application. Opting out won't affect your status. Message and data rates may apply. Reply STOP to unsubscribe or HELP for assistance. See our Privacy Policy for details.

ABOUT PLACER.AI: 

Placer.ai is transforming how organizations understand the physical world. Our location analytics platform provides unprecedented visibility into locations, markets, and consumer behavior. Placer empowers thousands of customers—from Fortune 500 companies, to local governments and nonprofits— to make smarter, data-driven decisions.
What sets us apart? We've built the most advanced location intelligence platform in the market while maintaining an uncompromising commitment to privacy, proving that powerful analytics and responsible data practices can coexist.
Our growth reflects the market's demand: we reached $100M in annual recurring revenue within just 6 years of launching, achieved unicorn status with a $1B+ valuation in 2022, and continue to expand rapidly as one of North America's fastest-growing tech companies. We're creating a $100B+ market opportunity, and we're just getting started.
Named one of Forbes America's Best Startup Employers and a Deloitte Technology Fast 500 company, we're building a culture where innovation thrives, collaboration is the norm, and every team member contributes to reshaping how the world understands location.
 

SUMMARY:

• As a Senior Big Data Engineer, working within Placer.ai's Mobility Group, you will play a pivotal role in designing, developing, and maintaining the data infrastructure that powers our location analytics platform.

RESPONSIBILITIES:

• Data Pipeline Architecture and Development: Design, build, and optimize robust and scalable data pipelines to process, transform, and integrate large volumes of data from various sources into our analytics platform.
• Data Quality Assurance: Implement data validation, cleansing, and enrichment techniques to ensure high-quality and consistent data across the platform.
• Performance Optimization: Identify performance bottlenecks and optimize data processing and storage mechanisms to enhance overall system performance and reduce latency.
• Cloud Infrastructure: Work extensively with cloud-based technologies (GCP and AWS), to design and manage scalable data infrastructure.
• Collaboration: Collaborate with cross-functional teams including Data Analysts, Data Scientists, Product Managers, and Software Engineers to understand requirements and deliver solutions that meet business needs.
• Data Governance: Implement and enforce data governance practices, ensuring compliance with relevant regulations and best practices related to data privacy and security.
• Monitoring and Maintenance: Monitor the health and performance of data pipelines, troubleshoot issues, and ensure high availability of data infrastructure.
• Mentorship: Provide technical guidance and mentorship to junior data engineers, fostering a culture of learning and growth within the team.

REQUIREMENTS:

• Strong hands-on Apache Spark experience — building and operating pipelines in production, not just familiarity
• Proficiency in PySpark or Scala for Spark development
• Proven track record delivering ETL pipelines and data integration at scale
• Solid SQL skills and command of data modeling concepts
• Cloud platform experience (AWS, GCP, or Azure) in a production data context
• Comfortable working with distributed systems and big data formats (Parquet, Delta Lake)

Nice to have:

• Experience with pipeline orchestration tools, particularly Apache Airflow
• Exposure to the geospatial or location analytics domain
• Familiarity with Hadoop ecosystem components
• Background in both Python and Scala (beyond Spark context)

WHY JOIN PLACER.AI? 

• Join a rocketship! We are pioneers of a new market that we are creating
• Take a central and critical role at Placer.ai
• Work with, and learn from, top-notch talent
• Competitive salary
• Excellent benefits

NOTEWORTHY LINKS TO LEARN MORE ABOUT PLACER 

• Placer.ai's $100M round C funding (unicorn valuation!)
• See our data in action at The Anchor
• Placer.ai in the news
• Video: About Placer for Commercial Real Estate
• Video Playlist: Placer Brand & Explainer Videos

Placer.ai is committed to maintaining a drug-free workplace and promoting a safe, healthy working environment for all employees.

Placer.ai is an equal opportunity employer and has a global remote workforce. Placer.ai’s applicants are considered solely based on their qualifications, without regard to an applicant’s disability or need for accommodation. Any Placer.ai applicant who requires reasonable accommodations during the application process should contact Placer.ai’s Human Resources Department to make the need for an accommodation known.

May 2026

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

Lyft is looking for experienced software engineers from a scope of disciplines. We are growing our team with people who want to build, improve and incorporate technologies that make the lives of our community more enriched. As an engineer at Lyft, you'll collaborate with teams like product, data science, analytics, and operations on code that empower us to iterate quickly, while focusing on delighting our riders and drivers.

As a Software Engineer for Lyft Ads - you will work on one of Lyft’s newest lines of business focused on building the world’s largest transportation media network. We build products that allow brands to engage with our unique audience throughout their transportation journeys and beyond. For this role we are seeking software engineers who are passionate about backend and data engineering. You will join our Ad Infra Engineering team and contribute to building the systems and pipelines powering our ad-serving, measurement and audience platform. We work on technologies that let brands engage with our unique audience throughout their transportation journeys. This role is a great opportunity for an early-career engineer to gain experience working with distributed backend systems and large-scale data workflows, collaborating closely with product, analytics, and data science teams.

Why Lyft Ads?

• Be part of a high-impact team building the foundations of Lyft’s advertising infra
• Gain experience working with complex systems at scale, backed by mentorship and growth opportunities.
• Join a supportive, inclusive environment focused on engineering excellence and business impact.

Responsibilities:

• Develop and maintain backend systems that support real-time ad serving, campaign management, and reporting.
• Design and implement scalable data models to support analytics, targeting, and measurement use cases.
• Build and maintain data pipelines that handle ingestion, transformation, and distribution of large volumes of advertising data.
• Work with orchestration frameworks (e.g., Airflow) to schedule and monitor reliable, production-grade data workflows.
• Collaborate with cross-functional partners to integrate internal and third-party systems via APIs and batch data feeds.
• Write clean, maintainable, and testable code following best practices (CI/CD, observability, code reviews).
• Participate in architecture discussions and design reviews with an emphasis on performance and reliability.
• Learn and grow through mentorship, documentation, and regular team collaboration.

Experience:

• BSc/MSc in Computer Engineering, Computer Science, related field or relevant work experience
• 3+ years of industry experience in backend or data engineering roles
• Proficiency in at least one backend programming language (e.g., Python, Go, Java)
• Good understanding of distributed systems, microservices, and database design (SQL and NoSQL).
• Exposure to orchestration tools (e.g., Airflow, Prefect) and data distribution technologies (e.g., Kafka, Pub/Sub).
• Experience working with relational and non-relational databases (e.g., PostgreSQL, BigQuery, DynamoDB).
• Experience with Linux.

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Toronto area is CAD $108,000 - CAD $135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

Summary:

The Cloud team at Lucid is currently seeking a Senior Site Reliability Engineering role. In this position, the individual will be responsible for providing
reliability to the cloud infrastructure that enabled Lucid Motors' cloud-based services and internal systems.

Responsibilities:

• Provide Reliability Engineering to cloud services deployed and managed in the region of KSA.
• Continuous delivery (CI/CD) using ArgoCD, Jenkins, Maven, and Docker.
• Architect cloud systems in highly available design, ensuring Disaster Recovery (DR) measures are in place.
• Containerization and deployment of microservices and data pipeline on Kubernetes using Helm installation.
• Advocate for a DevOps culture of automation and engineering best practices to enable development teams.
• Auto-scale and monitoring performance for Kubernetes and running applications using Prometheus and Grafana or similar tools.
• Performing SRE activities such as availability and reliability monitoring and reports.
• Deploy, configure and maintain tools such as Kafka, Spark, Trino, Airflow, MQTT, and Microservices.
• Setting up infrastructure as a service using Terraform.
• Work and deploy using the codebase repositories in GitLab, along with participation in the peer review activities.
• Support No-SQL databases such as Elastic Search, Mongo, Cassandra, and other open sources services.
• Setup and monitor various applications and services. Continuously enhance the alerts and automate the recovery process.
• Articipate in the on-call rotation to keep up the service SLA per the business needs.
• Work with Product Owners, engineering managers, and other team members in Agile Scrum and Kanban mode.
• Take appropriate actions by doing impact analysis during the incidents.

Requirements and Skills:

• B.S. or M.S. degree in Computer Science, Engineering, or equivalent field.
• Can speak English fluently to communicate with teams across geographical regions.
• +6 years of experience in SRE or DevOps Engineering.
• +5 years of experience deploying and maintaining systems on Oracle cloud (OCI), and Amazon web services (AWS).
• +3 years of experience in Terraform.
• +3 years of experience in Kubernetes.
• +3 years of experience with tools such as Jenkins, ArgoCD, etc. to build automation and CI/CD pipelines.
• Professional experience in Programing or scripting languages using Python, Go, Bash/Shell, or others.
• Experience in administrative operations knowledge in RDBMS (e.g. PostgreSQL, MySQL), and NoSQL databases (e.g. MongoDB).
• Moderate experience in distributed computing for running data systems using Spark, Hive, Zookeeper, and Kafka.
• Moderate experience in debugging tools and troubleshooting performance bottlenecks at the infrastructure or at the application tier.
• Good to have experience with Config Management using Ansible, Chef, Puppet, or others.

Company Background

Our client is a global technology company transforming the way brands and agencies make marketing decisions. Its platform enables marketers to plan and activate cross-channel, programmatic media campaigns using real-time research, proprietary audience data, advanced analytics, and more than 150 integrated partners including Facebook, Instagram, Pinterest, Snapchat, and Twitter. The company operates across North America, Europe, the Middle East, Asia, and Australia.

Project Description

Data Management Platform is the core system that receives, processes and provides information to other external DMPs and real time platforms. The purpose of DMP is to store the connection between users/devices and their respective behavioral categories. Further this data is used by the other teams for the analytics and digital ad targeting. Team roadmap includes developing a new system based on the streaming architecture with a relevant tech stack.

Technologies

• Spark
• Scala
• Vertica
• Kafka
• Airflow
• K8S
• Python, Java (preferable)

What You'll Do

• Own end-to-end development, from design to production, with a focus on innovation and efficiency;
• Lead and mentor developers on complex projects impacting core business systems;
• Contribute to the design and development of next-generation data solutions;
• Implement high-scale big data solutions and contribute to platform infrastructure and architecture;
• Research and evaluate core technologies, integrations, and external APIs;
• Collaborate with cross-functional stakeholders, including Product, Engineering, and data providers;
• Participate in an off-hours pager duty rotation;

Job Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, or equivalent experience;
• 4+ years of software development experience;
• 2+ years of experience with Apache Spark;
• 2+ years of experience with Scala (preferred) and/or Python or Java;
• Experience working with high-performance, large-scale, or distributed data systems;
• Experience with SQL and NoSQL databases;
• Experience with Kubernetes;
• Experience with Git;
• Experience building and optimizing data pipelines, ETL processes, and streaming systems (e.g., Hadoop, Spark, Kafka) is a plus;
• Familiarity with tools such as GitLab, Grafana, InfluxDB, and Kibana is a plus;
• Strong communication skills and ability to work effectively in a team;
• English level: B1+ or higher;

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.

About Us

Camus Energy builds software solutions that help new load and generation connect to the grid faster—without sacrificing reliability.

As electricity demand accelerates and clean energy scales, traditional interconnection processes are becoming the bottleneck. Utilities and developers face growing queues, long timelines, and costly upgrades that slow progress across the grid.

Camus enables flexible grid connections that allow new load and generation to connect sooner by planning for and operating within real system constraints. Our platform bridges the gap between grid operators and large load developers, providing a view of time-varying grid capacity for any given new interconnection point. 

We combine high-reliability software experience from companies like Google and Meta with deep power systems expertise across the utility sector. If you’re excited to work at the intersection of infrastructure, software, and climate, we’d love to hear from you.

The Role

We're looking for a Machine Learning Engineer to own and advance the forecasting and predictive modeling capabilities at the heart of the Camus platform. This is an individual contributor role with real technical depth and product influence; you'll be responsible for the full lifecycle of ML model development, from exploratory analysis and model design through to production deployment and monitoring. 

This is not a role where the problem statements are handed to you. You'll work directly with Camus’ teams and external stakeholders to understand their data, define the right questions, and translate messy real-world signals into reliable, production-grade data driven analytics. You'll bring that ground-truth perspective back into product decisions, and work closely within the Engineering team to integrate ML models into our planning and operational workflows. 

The forecasting and predictive modeling problems we're solving often don't have off-the-shelf answers. We work as a tight, technical team that moves with urgency but builds with the discipline that production-grade software demands. If you want to do the most technically interesting ML work in the clean energy space while directly shaping how it becomes a product, this is the role.

What You'll Do

• Design, train, and evaluate predictive ML models with a focus on forecasting and time-series applications
• Conduct exploratory data analysis, feature engineering, and statistical modeling across large structured and unstructured datasets
• Collaborate with Engineering to define ML infrastructure requirements, and deploy and integrate ML models into operational workflows and decision-support tools
• Work cross-functionally with Camus teams to define problem statements and translate business objectives into ML solutions
• Communicate model performance, uncertainty, and limitations clearly to both technical and non-technical audiences
• Champion ML best practices around reproducibility, versioning, and testing

What You'll Bring

• PhD with 3+ years of industry experience, Masters with 5+ years, or Bachelors with 8+ years in Machine Learning, Statistics, Computer Science, Applied Mathematics, or a related quantitative field
• Demonstrated track record of delivering ML models into production environments
• Experience with time-series forecasting methods — including classical approaches (e.g. ARIMA) and modern ML-based methods (e.g. gradient boosting or temporal neural networks) 
• Strong proficiency in Python and core ML/data science libraries (PyTorch, scikit-learn, statsmodels, pandas, etc.)
• Experience with probabilistic forecasting, uncertainty quantification and backtesting
• Ability to translate ambiguous business problems into well-scoped ML projects
• Comfortable operating with autonomy in a small team, balancing speed of delivery with the engineering discipline that production-grade software demands.

Nice to Have

• Experience in the energy sector — e.g. load forecasting, renewable generation prediction, price modeling or grid operations
• Experience with MLOps tooling and infrastructure: cloud platforms, containerization, and model serving patterns 
• Experience with data pipeline tooling, e.g. Airflow, Spark, or Databricks 
• Able to leverage AI code development tools to accelerate development

What We Offer

• Competitive base salary
• Comprehensive benefits, including FSA and 401k for full time employees
• Fully remote workplace with options for in office work in the Bay Area
• Flexible PTO, which we encourage you to use!
• A real impact on climate change - we’re building the world we want to live in and we want you to join us!

The expected base salary for this role is $180,000 - $230,000 annually, depending on experience, skills, and qualifications.

Role & Team

As a Data Engineering Manager, you will lead across several cross-functional teams, managing up to ~10 data engineers and GIS specialists. You will support teams working on data processing and pipelines to enable ML-powered product capabilities.

Our product teams are cross functional and will typically include product managers, designers, engineers and subject matter experts relating to the team’s domain.

You will be accountable for the technical direction and delivery outcomes of your area. You will challenge your teams to pursue ambitious goals while providing a high level of support — growing engineering talent and fostering a highly collaborative, team-based environment where people can do great work.

Your primary focus will be on building high-performing teams and driving results through others. You will not be expected to spend significant time doing hands-on coding; however, you will be expected to dive deep technically when required and leverage your experience to support strong technical decision-making.

Time zone requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)

What You'll Do

• Enable our data engineers to become highly productive members of their cross-functional teams, empowering them to ship high-quality, reliable data platforms and pipelines on a daily basis.
• Grow the teams by attracting great talent from your network.
• Foster an inclusive and caring culture where everyone can do their best work.
• Provide regular 1:1 coaching and feedback to tap into the potential of all your team members and help them thrive and reach their aspirations.
• Be a strategic partner to product managers, machine learning engineers, and other stakeholders within your domains and ensure that we are making the correct data architecture and platform decisions that balance short and long term goals.
• Ensure suitability of the data architecture, pipelines, and data models within your domains to enable longer term product, analytics, and machine learning goals.
• Work closely with the other Product & Engineering leaders on strategy, technology and people, including improving our data engineering practices and introducing capabilities that can accelerate data access, reliability, and unlock new product and data-driven opportunities

Skills & Experience

• Experience working in a high growth scaleup environment
• Passionate about climate
• Product minded and able to demonstrate significant impact you have had on a business through the application of data platforms and data-driven systems
• 2+ years experience leading and managing data engineers across multiple teams
• Experience working with the following (or similar) technologies: Python, SQL, data pipeline orchestration tools (e.g., Airflow, Dagster), data warehouses/lakehouses, Postgres DB, data pipelines
• Ability to unblock your team by contributing at a senior engineering level (e.g., reviewing data models, debugging pipelines, guiding architecture). How hands-on you'll be in this role will depend on team size and maturity
• Comfortable working in a build it, run it environment (GCP, cloud run, grafana, k8s) - or similar, with an understanding of data reliability, observability, and pipeline operations
• Strong leadership skills with the ability to mentor and coach engineers at all levels
• Excellent communication skills and ability to collaborate effectively in a cross-functional team environment
• Passion for learning and staying updated with evolving technologies and industry trends, particularly in data engineering and data infrastructure

Nice To Have

• Experience working with maps/imagery/geospatial domains  

Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.

What We Offer

• Competitive, location-specific compensation and benefits 
• Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
• Home office stipend, coworking and ongoing education budgets 
• A company culture that genuinely embodies each of our core values
• To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis

About the Role

Together AI is building high-performance inference compute and the software platform around it. We’re looking for an early-career Data Warehouse Engineer with strong fundamentals and high growth potential to grow into a technical lead over time. You’ll contribute to designing and operating our data warehouse, ETL pipelines and orchestration, work on core data models and metrics, and help raise the bar on data quality and governance across the org — with mentorship and support from experienced engineers.

Requirements

• 0–4 years of professional experience (or strong internships/projects) working with data warehouses, pipelines, or analytics engineering.
• Solid SQL fundamentals — you’re comfortable writing queries and have some exposure to window functions or dimensional modeling concepts.
• Some hands-on experience with dbt or Airflow, or strong eagerness to learn — coursework and personal projects count.
• Basic Python for scripting and data tooling; any exposure to Spark (PySpark/SQL) is a plus.
• Familiarity with data modeling concepts like SCD2 or star schemas — even if only from coursework.
• Good communication skills: you can ask clarifying questions, explain your reasoning, and work with stakeholders to understand their needs.
• High standards for data quality, reliability, and maintainability — you care about getting things right.

Responsibilities

• Contribute to building and maintaining a medallion/curated data warehouse stack (bronze/silver/gold) for product, usage, billing, and operational data.
• Build and maintain Airflow orchestrated pipelines and dbt transformation projects (modular, tested, documented).
• Help design analytics-ready models: SCD Type 2, star schemas, and appropriate normalization for upstream canonical layers.
• Learn and apply Master Data Management (MDM) patterns (golden records, reference data, deduping, identity resolution).
• Implement data quality checks (freshness, nulls, referential integrity, distribution drift, anomaly detection).
• Contribute to data governance habits: data stewardship, ownership, SLAs, and clear definitions for “source of truth.”
• Help build and maintain a business semantic layer (consistent metric definitions, dimensions, and reusable logic) used by notebooks/BI.
• Partner with stakeholders (Product, Engineering, Finance, GTM, Ops) to translate questions into durable datasets and metrics.
• Use SQL, Python, and Spark where scale demands it; optimize for correctness, performance, and cost.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $130,000 - $170,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

Together AI is building high-performance inference compute and the software platform around it. We’re looking for an early-career Data Warehouse Engineer with strong fundamentals and high growth potential to grow into a technical lead over time. You’ll contribute to designing and operating our data warehouse, ETL pipelines and orchestration, work on core data models and metrics, and help raise the bar on data quality and governance across the org — with mentorship and support from experienced engineers.

Requirements

• 0–4 years of professional experience (or strong internships/projects) working with data warehouses, pipelines, or analytics engineering.
• Solid SQL fundamentals — you’re comfortable writing queries and have some exposure to window functions or dimensional modeling concepts.
• Some hands-on experience with dbt or Airflow, or strong eagerness to learn — coursework and personal projects count.
• Basic Python for scripting and data tooling; any exposure to Spark (PySpark/SQL) is a plus.
• Familiarity with data modeling concepts like SCD2 or star schemas — even if only from coursework.
• Good communication skills: you can ask clarifying questions, explain your reasoning, and work with stakeholders to understand their needs.
• High standards for data quality, reliability, and maintainability — you care about getting things right.

Responsibilities

• Contribute to building and maintaining a medallion/curated data warehouse stack (bronze/silver/gold) for product, usage, billing, and operational data.
• Build and maintain Airflow orchestrated pipelines and dbt transformation projects (modular, tested, documented).
• Help design analytics-ready models: SCD Type 2, star schemas, and appropriate normalization for upstream canonical layers.
• Learn and apply Master Data Management (MDM) patterns (golden records, reference data, deduping, identity resolution).
• Implement data quality checks (freshness, nulls, referential integrity, distribution drift, anomaly detection).
• Contribute to data governance habits: data stewardship, ownership, SLAs, and clear definitions for “source of truth.”
• Help build and maintain a business semantic layer (consistent metric definitions, dimensions, and reusable logic) used by notebooks/BI.
• Partner with stakeholders (Product, Engineering, Finance, GTM, Ops) to translate questions into durable datasets and metrics.
• Use SQL, Python, and Spark where scale demands it; optimize for correctness, performance, and cost.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $130,000 - $170,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

You’ll join the Data Platform team, responsible for building the backend services and “data products” that power how data moves through the company. We create the core platform primitives — high-quality event streams, reliable access layers, and developer-friendly APIs/tools — so teams across the org can self-serve what they need and ship faster. You’ll contribute to backend services that create value from our company data, and help make our data platform more self-serve so product and engineering teams can easily create and operate event-driven architectures, publish/consume streams, define access models, and ship data products end-to-end. You’ll also work on LLM-adjacent services such as prompt categorization/taxonomy, enrichment, and metadata systems that turn raw telemetry into trusted, usable products — with mentorship and support from experienced engineers.

Responsibilities

• Contribute to backend services that enhance the data platform’s capabilities (APIs, control planes, automation, governance).
• Help enable DIY workflows for teams across the company:

• • Define/publish events and schemas
  • Create/consume streams and subscriptions
  • Establish access models (authz, row/field-level controls where applicable)
  • Manage dataset/catalog metadata, lineage, versioning, and retention

• Contribute to end-to-end data products: ingestion → validation/quality → enrichment → serving (APIs/streams) → observability → adoption.
• Work on prompt categorization and enrichment services: taxonomy design, labeling workflows, classifier/rules integration, evaluation, drift/quality monitoring, and safe rollouts.
• Learn to own reliability: SLOs, alerting, performance/cost tuning, incident response, and postmortems.
• Partner cross-functionally with ML/LLM, infra, security, and product teams to define crisp contracts and deliver durable platform primitives.

Requirements

• 0–4 years building production or project-based backend systems (internships, coursework, and personal projects count).
• Solid fundamentals in at least one backend language (e.g., Go, Python, Java, Rust) and some exposure to API design (REST).
• Eagerness to own work end-to-end: design docs, implementation, testing, deployment, and iteration based on real usage.
• Strong engineering fundamentals: clean, maintainable code, thoughtful abstractions, and a desire to build systems that are easy to evolve.
• Basic data modeling and SQL skills, and some familiarity with at least one of:

• • Streaming/eventing (Kafka/PubSub/Kinesis, etc.)
  • Workflow/compute (Airflow/Spark/Flink/Trino, etc.)
  • OLTP/OLAP stores and data lakes (Postgres + warehouse/lake tech)

• AI augmentation curiosity:

• • You’re curious about how engineers use AI/LLMs to build software faster and better (e.g., coding copilots, agentic workflows, retrieval/knowledge grounding), and you’re eager to apply this to your own work.
  • You understand that AI tools can fail or create issues, and you’re thoughtful about when and how to apply them.

Nice to have

• Any exposure to self-serve platforms, developer tooling, or multi-tenant services.
• Coursework or projects involving LLM/AI products: prompt/response telemetry, eval datasets, embeddings/RAG metadata, model/tool traces, privacy-safe logging.
• Passion for good quality code, highly readable, SOLID principles, design patterns, Domain Driven Design.
• Awareness of security and governance basics: least-privilege access, auditability, data retention, PII handling.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $120,000 - $170,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

The Role

Join us in revolutionizing the lending landscape. SoFi is seeking enthusiastic Senior Software Engineers who are ready to lead the development of key advancement to the next generation of our financial services platform. 

Data Foundations leads the path on building the central platform-level foundation and infrastructure that powers SoFi's entire data ecosystem. Their scope spans Infrastructure & Core Primitives and Platform Operations — essentially the backbone that enables all data capabilities across the organization. Key qualifications of this role include:

• Leading the technical evolution of one or more key platform subsystems.
• Resolving problems in the platform design and implementation that weren’t clearly anticipated, taking requirements with ambiguity and proposing durable technical solutions.
• Expertly leverage existing solution patterns and understand when to differentiate resulting in well-structured, maintainable code.
• Ability to understand data models, APIs, scaling concerns, and failure modes in order to make effective trade-offs between maintainability and performance.
• Creating stability by writing meaningful tests, considering observability, and leveraging your ability to debug complex issues across multiple system layers.
• The ability to create clear design and operational documentation.
• Contributes to code reviews, is a role model for more junior engineers, and contributes to team efficiency, beyond personal output.

What You’ll Do

As an emerging leader within our team, you will focus on building out the backend services for our next-generation Lending Platform. This role involves full product lifecycle engagement, from initial concept to deployment. Key responsibilities include implementing new capabilities, ensuring code quality, and delivering highly-available, scalable services. Success requires close technical collaboration with Product, Marketing, Operations, Business, Legal, and Compliance teams. You will be responsible for translating business requirements from these stakeholders into effective technical solutions that provide outstanding value to our members.

What You’ll Need

• Bachelor's or Master's degree in Computer Science, or Software Engineering
• 3+ years as a professional, full-time Software Engineer, or similar relevant work experience.
• Proficient coding in Java, Kotlin, or other similar object-oriented programming language.
• Proficient working with GIT and related CI/CD systems.
• Experience with public cloud compute, storage, and infrastructure.
• Experience with any data warehousing solution like Snowflake and IAC tools to provision platform infrastructure.
• Experience with Kafka, Docker, Kubernetes, and Spring Boot or similar frameworks.
• Deep understanding of relational and document database fundamentals.
• Deep understanding of fundamental distributed systems concepts.

Nice To Have

• Full-Stack experience in both back-end (Kafka, Redis, Docker) and front-end (JavaScript, TypeScript, React).
• Experience with microservices design principles and architecture.
• Experience with workflow orchestration technology (AWS step function, Airflow, Temporal).

We're driven to push boundaries and deliver exceptional products to help our members achieve financial stability. If you have the passion and a commitment to customer success, we want to hear from you.

Overview

At PrizePicks, we are changing the game in daily fantasy sports. We are a passionate team of innovators dedicated to creating a best-in-class experience for our members. Our engineering team builds and scales the platform that powers our explosive growth, from real-time contest engines to the services that handle millions of daily transactions. We are looking for a Senior Software Engineer to join our Social Experience team and help us continue to build the future of fantasy sports.

Job Summary

We are seeking a Software Engineer III with strong Ruby on Rails expertise to join our Marketing Technology (MarTech) team. In this role, you will own feature development within Rails-based backend services that power PrizePicks' member engagement, lifecycle marketing, and marketing enablement infrastructure - including data pipelines, customer data platform integrations, and marketing automation tooling. You will own the delivery of complex work end-to-end, begin guiding junior engineers, and contribute to architectural decisions that shape your team's systems. This is a role for someone who can bridge the gap between technical systems and marketing outcomes, deliver high-quality solutions, and start having influence beyond their own code.

What You'll Do

• Own feature development: Take ownership of features end-to-end - from technical design through delivery - breaking complex projects into well-scoped, deliverable pieces across our martech stack.
• Write high-quality code: Produce Ruby code that is idiomatic, performant, well-tested, and raises the bar for the codebase.
• Contribute to architecture: Participate in team-level architectural decisions around data modeling, CDP event schemas, service boundaries, API design, and background processing patterns.
• Build and maintain martech integrations: Design and own integrations with our Customer Data Platform (CDP) and marketing automation tools like Braze - including event ingestion, audience syncing, and canvas triggering via API.
• Improve quality proactively: Identify opportunities to improve data reliability, pipeline performance, and developer experience - and act on them.
• Guide junior engineers: Provide technical guidance to Software Engineers I and II through thorough code reviews, pairing sessions, and design feedback.
• Collaborate cross-functionally: Work closely with Marketing, Data, and Product teams to translate campaign and personalization requirements into reliable technical implementations. You should be comfortable sitting in a room with a marketer and speaking their language.
• Participate in on-call rotation: Take increasing ownership of incident response, contributing to root cause analysis and systemic improvements.
• Build team knowledge: Document technical decisions, data models, and integration patterns to strengthen your team's shared understanding.

What You Have

Experience

• 3–5 years of professional software engineering experience, with meaningful time building Ruby on Rails applications
• Hands-on experience working with a Customer Data Platform (Rudderstack, Segment, mParticle, or similar) — you understand how event tracking, identity resolution, and audience building work in practice
• Experience integrating with marketing automation platforms such as Braze, Iterable, or Klaviyo, including direct API usage (not just clicking buttons in a UI)
• History of delivering complex features within a software team to drive business outcomes
• Experience breaking down ambiguous requirements — including those coming from non-technical stakeholders like marketers — into concrete technical plans
• Exposure to large-scale, high-throughput distributed systems — you understand the challenges of building software that serves millions of users in real time

Technical Skills

• Advanced proficiency in Ruby on Rails — you understand the framework deeply and write clean, idiomatic, production-quality code
• Strong PostgreSQL skills — schema design, query optimization, migrations, and understanding of performance characteristics at scale
• Experience designing and building RESTful APIs within Rails
• Solid data engineering fundamentals: pipeline design, event schema management, and working with high-volume data flows are areas where you're comfortable
• Solid testing practices — RSpec or Minitest, unit, integration, and end-to-end testing strategies
• Familiarity with background job processing (Sidekiq or similar)
• Familiarity with containerization (Docker) and orchestration (Kubernetes)
• Understanding of CI/CD pipelines and deployment workflows

Working Style

• Autonomous — you can take an ambiguous problem and drive it to a well-defined solution
• Comfortable providing and receiving direct technical feedback
• Strong written communicator, especially important in a fully remote environment
• Able to context-switch between deep technical work and collaborative conversations with marketing stakeholders

What Makes You Stand Out

• Experience using AI-assisted development tools for coding, planning, and scoping work
• Experience with agentic coding tools and AI-augmented development workflows
• Prior experience working in a remote engineering organization
• Deeper data engineering background — experience with tools like dbt, Spark, Airflow, or building analytical pipelines in a data warehouse environment
• Experience building or maintaining a user segmentation or audience management system
• Familiarity with identity resolution concepts (device graphs, deterministic vs. probabilistic matching)
• Experience supporting experimentation in marketing surfaces (holdout groups, A/B tests, send-time optimization)
• Working knowledge of compliance considerations around user data in marketing contexts (CAN-SPAM, TCPA, CCPA)

Where You’ll Live

• This a remote position anywhere in the US is fine. #LI-REMOTE

Working at PrizePicks:

The typical salary range for this position is $145,000 to $155,000 At PrizePicks, we consider your role, level, and where you'll be working when determining our salary ranges. The compensation info you see on our job postings gives you an idea of the starting pay range for the position. Your actual pay within that range will depend on your specific work location, as well as your skills, experience, and education. Your recruiter will be happy to chat more about the specific pay range for your location and how we arrived at it during the hiring process. 

This application period will remain open for 30 days. We’re committed to finding the best candidate, so this date may be adjusted, and any changes will be reflected in this posting. 

Date Posted: May 8, 2026

First Extension: June 7, 2026

Second Extension: July  7, 2026

About Life360

Life360’s mission is to keep people close to the ones they love. Our category-leading mobile app, Tile tracking devices, and Pet GPS tracker empower members to protect the people, pets, and things they care about most with a range of services, including location sharing, safe driver reports, and crash detection with emergency dispatch. Life360 serves approximately 91.6 million monthly active users (MAU), as of September 30, 2025, across more than 180 countries.

Life360 delivers peace of mind and enhances everyday family life with seamless coordination for all the moments that matter, big and small. By continuing to innovate and deliver for our customers, we have become a household name and the must-have mobile-based membership for families (and those friends who are basically family).

Life360 has more than 500 (and growing!) remote-first employees. For more information, please visit life360.com.

Life360 is a Remote-First company, which means a remote work environment will be the primary experience for all employees. All positions, unless otherwise specified, can be performed remotely (within the US) regardless of any specified location above. 

We are AI Native 

We are building an AI native company where AI is an integral part of how we build and operate. AI tool usage during interviews varies by role. You may be asked to demonstrate proficiency with AI tools, discuss how you leverage AI, or complete interview exercises without AI assistance. Your Recruiter will provide clear guidance as you move through the interview process.
Undisclosed use of AI not previously discussed with or approved by your Recruiter may impact your candidacy.

About The Team

The Finance Data Team sits at the intersection of Finance & Accounting teams and Life360’s data. We provide the data ingestion / processing / reporting / egress needed by our partner teams in Finance & Accounting to enable their work and ensure SOX compliance with rigor. We push the envelope on how work is done through implementation of AI tools and capabilities to enhance our own pace of development and capabilities that we deliver to our stakeholders.

We are hiring a bar-raising Staff Data Engineer to drive our ingress / egress capabilities and build cross-cutting capabilities to drive developer experience and security. This role requires someone who can step into ambiguity, make sound architectural decisions, eliminate operational fragility, and establish an engineering discipline that others adopt.

You will serve as a technical reference point - shaping standards, influencing cross-team architecture, and driving initiatives to clear, production-ready outcomes. We value engineers who are direct, collaborative, and proactive in surfacing risks early, while helping build a team culture where high standards and psychological safety coexist.

About the Job

The Life360 Finance Data Team works as the integrator for numerous systems - bringing data into the Finance Data Warehouse, transforming it, and pushing it to its relevant destinations (reporting, data asset deliverables, tools, etc).  To support our role we are continuously building and enhancing our system - adding new data, new transformations, and new tooling to improve developer velocity and ‘buy down’ overhead costs associated with maintaining our system.

As a Staff Data Engineer you will drive forward the:

• Data ingestion suite - a mix of capabilities ranging from Fivetran to completely custom connectors that bring data into our warehouse and monitor for data quality.
• Data transformation suite - enhancing our dbt environment (dbt core) and the suite of tools that we leverage to build data models, semantic models, and other interfaces.
• Data egress suite - a mix of capabilities that allow us to push data to its end destinations.
• CI/CD pipelines and other tools / capabilities to enhance the developer experience and velocity.
• Infrastructure and networking behind our warehouse and related connectors.
• Databricks configuration and capabilities.
• Security posture and access controls.

The ideal candidate:

• They have spent years building out data platforms / infrastructure as well as creating ingress / egress data frameworks that are used in pipelines.  They have tackled numerous challenges and found novel solutions to problems for data ingestion, processing, and egress.
• They have learned how to leverage LLMs for development velocity and analytics - not just asking it to write the code but leveraging the tools to support their development under clear guidance and accepts ownership of the work produced as their own.
• They have learned to think about scalability / velocity / experience of future development and not just shipping the current project.
• They are part software engineer, part data integration engineer, and part data platform engineer.
• They adhere to the controls / procedures / separation of duties necessary to maintain our SOX compliance.

We are looking for someone with strong engineering depth who demonstrates ownership, decisiveness, and the ability to elevate both the system and the team around them.

For candidates based in the US, the salary range for this position is $190,000 to $280,500 USD. For candidates based out of Canada, the salary range for this position is $220,000 to $260,000 CAD. We take into consideration an individual's background and experience in determining final salary; therefore, base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience. The compensation package includes a wide range of medical, dental, vision, financial, and other benefits, as well as equity.

AI / LLM Usage

The Finance Data Team leverages LLM’s to support code generation, analysis, and other use cases.

• Cursor / Claude Code.
• Other tools (Wispr Flow, Claude & Claude Cowork, Gemini / Codex).

Your experience with AI / LLM usage should include managing code generation with a close eye on quality, standards, and testing - owning the outputs as your own.  Your work with and ability to leverage these tools will drive your velocity and ability to effectively work within our environment.

What You’ll Do

• Architect and evolve scalable data ingestion and egress frameworks and pipelines that are well tested and offer strong data quality monitoring. 
• Architect and evolve our CI/CD processes - enhancing the testing environment and observability (such as building LLM-driven reviews with context awareness through data diffing, lineage analysis / downstream impact analysis, and general context).
• Architect delivery architecture of data assets to external team partners to reduce manual operational overhead associated with month end close.
• Enhance our Claude Code / LLM development support capabilities - creating tools / skills / agents that give our LLMs more context and help us continually improve their abilities to debug, create code, and maintain systems.
• Enhance our security posture in our AWS / Databricks environment.
• Design and implement distributed data processing systems using Spark and Databricks on AWS.
• Establish clear ingestion and integration boundaries that eliminate single points of failure.
• Proactively surface risks, dependencies, and tradeoffs before they impact delivery.
• Produce clear technical artifacts and recommendations for stakeholders and leadership.
• Design logical and physical data models balancing flexibility, performance, governance, and scalability.
• Partner closely with the Analytics Engineers on the Finance Data Team to support high-quality downstream data modeling & reporting.
• Harden pipelines with monitoring, alerting, SLAs, and recovery mechanisms.
• Mentor engineers and elevate distributed systems rigor across the team.

What We’re Looking For

• 8+ years designing and operating high-volume distributed data systems in production.
• Deep expertise with a cloud data platform (Databricks strongly preferred) and AWS from an infrastructure / services architecture, deployment, and ownership perspective.
• Strong proficiency in Python, SQL, and Spark for large-scale processing.
• Strong proficiency with modern CI/CD practices (creating GitHub Actions, writing Terraform code to manage infrastructure in Databricks / Airflow / AWS / and others).
• Hands-on experience with dbt from an infrastructure / deployment perspective and understanding of how platform decisions impact downstream modeling.
• Strong grasp of data modeling, partitioning strategies, storage formats, and analytical workload optimization.
• Experience with Airflow and data flow orchestration.
• Experience with networking challenges in data ingestion (e.g., VPC peering, firewall traversal, API rate limiting, cross-AWS account access, etc.)
• Able to effectively leverage / oversee LLM-supported code development while maintaining a high quality bar.
• Demonstrated experience with AI tools to support / enhance development - Claude Code, Cursor, etc.
• Demonstrated ability to independently scope ambiguous problems and drive them to decisive outcomes.
• Track record of proactively escalating risks and closing long-running efforts with clear recommendations.
• Experience defining ingestion validation standards and implementing data quality controls.
• Proven ability to reduce operational fragility and eliminate single points of failure.
• Strong systems design skills across distributed and event-based architectures.
• Demonstrated technical leadership influencing cross-team architectural decisions.
• Excellent communication skills across engineering, analytics, product, and executive stakeholders.
• BS in Computer Science, Engineering, Mathematics, or equivalent experience.

Our Benefits

• Competitive pay and benefits.
• Medical, dental, vision, life and disability insurance plans (100% paid for US employees). We offer supplemental plans for medical and dental for Canadian employees.
• 401(k) plan with company matching program in the US and RRSP with DPSP plan for Canadian employees.
• Employee Assistance Program (EAP) for mental wellness.
• Flexible PTO and 12 company wide days off throughout the year.
• Learning & Development programs.
• Equipment, tools, and reimbursement support for a productive remote environment.
• Free Life360 Platinum Membership for your preferred circle.

Life360 Values

Our company’s mission-driven culture is guided by our shared values to create a trusted work environment where you can bring your authentic self to work and make a positive difference 

• Be a Good Person - We have a team of high-integrity people you can trust. 
• Be Direct With Respect - We communicate directly, even when it’s hard.
• Members Before Metrics - We focus on building an exceptional experience for families. 
• High Intensity, High Impact - We do whatever it takes to get the job done. 

Our Commitment to Diversity

We believe that different ideas, perspectives, and backgrounds create a stronger and more creative work environment that delivers better results. Together, we continue to build an inclusive culture that encourages, supports, and celebrates the diverse voices of our employees. It fuels our innovation and connects us closer to our customers and the communities we serve. We strive to create a workplace that reflects the communities we serve and where everyone feels empowered to bring their authentic best selves to work.

We are an equal opportunity employer and value diversity at Life360. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any legally protected status.  

We encourage people of all backgrounds to apply. We believe that a diversity of perspectives and experiences creates a foundation for the best ideas. Come join us in building something meaningful. Even if you don’t meet 100% of the qualifications above, you should still seriously consider applying!

#LI-Remote

____________________________________________________________________________

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

We are experts in data, working to make it cost-effective, understandable, and trustworthy. We build pipelines processing billions of events a day and are stewards of canonical data warehouses and datasets delivering products for Stripe Users while embedding with teams to build their data products.  We are experts in using the Stripe Data Platform and to scale we lead the data culture and data education to enable product teams to own their data. We invest in [AI] Data Ops to scale incident handling and serve as an escalation path for data incidents to minimize their impact. The Data Engineering Solutions team will work closely with product teams delivering trustworthy data / backend code / and innovative (AI) tools/platforms/services for data.

What you’ll do

We're looking for a person who could drive the Data Engineering Solutions Team in solving high-impact, cutting-edge data problems. The ideal candidate will be someone that has built data pipelines for large scale volume, is deeply knowledgeable of Data Engineering tools including Airflow/Spark/Kafka/Flink, is empathetic, excels at building strong relationships, and collaborates effectively with other Stripe teams to understand their use cases and unlock new capabilities.

You will:

• Lead the technical outcomes for a team of ambitious, talented engineers, providing mentorship, guidance, and support to ensure their success.
• Partner with our recruiting team to attract and hire top talent.
• Deliver cutting-edge data pipelines that scale to users' needs, focusing on reliability and efficiency.
• Develop strong subject matter expertise and manage the SLAs of data pipelines and full stack web applications that support critical stakeholders.
• Collaborate with product managers and peers across the company to create/improve canonical datasets and data warehouses, use golden paths, and ensure Stripes and customers are using trustworthy data.
• Leverage AI/LLM and Agents at scale to produce and analyze high-quality data on ambiguous problems
• Have an opportunity to work with Spark, Flink, Kafka, Trino, Pinot, Airflow, Scala, Java, SQL, and Python and many other big data technologies.
• Have the opportunity to drive the execution of key data initiatives for Stripe, overseeing the entire development lifecycle from planning to delivery while maintaining high standards of quality and timely completion.
• Foster a collaborative and inclusive work environment, promoting innovation, knowledge sharing, and continuous improvement within the team.

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

We’re looking for someone who has: 

• 10+ Years of engineering experience with 5+ Years of hands-on experience building+operating data systems/pipelines, datasets/data warehouses, infrastructure, and leading small teams to deliver exceptional solutions.
• A strong engineering background and passion for data.
• Prior experience with writing and debugging data pipelines using a distributed data framework (Spark / Hadoop / Trino / etc)
• An inquisitive nature in diving into data inconsistencies to pinpoint issues, and resolve deep rooted data quality issues
• Knowledge of a backend development language (such as Scala, Java, or Go) and strong SQL experience
• Extreme customer focus, with a commitment to partnering with Product Managers, leaders, and other Stripe engineers to understand their use cases.
• Effective cross-functional collaboration, with the ability to think rigorously, communicate clearly, and make or coordinate difficult decisions and trade-offs.
• Thrive with high autonomy and responsibility in an ambiguous environment.
• Ability to foster and work in a healthy, inclusive, challenging, and supportive work environment.

Preferred qualifications

• Expertise in Iceberg, Kafka, Change Data Capture, Flink, Spark, Airflow, Hive Metastore, Pinot, Trino, AWS Cloud, and influencing open-source contributions is a plus.
• Experience creating and maintaining Data Marts / Data Warehouses to power business reporting needs
• Experience working with Product or Go-To-Market (GTM - Sales/Marketing) teams
• Genuine enjoyment of innovation and a deep interest in understanding how things work, with the ability to question and direct architectural decisions.
• Strong written and verbal communication skills for various audiences, including leadership, users, and company-wide.

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team 

The Big Data Infrastructure operates the critical infrastructure that powers the batch data processing at Stripe. The team supports a variety of use cases, including Payment, Ledger, ML, Fraud Detection, Product Analytics, Regulatory Reporting, Financial Data Reconciliation, and externally facing products like Radar and Sigma. As an example of the scale, the team’s systems serve hundreds of teams, thousands of workflows, 100,000+ task executions, O(billion) transformations, and moving terabytes of data processing over 1 GB/second every day. Our users inside Stripe include other engineering teams, Data Scientists, Sales & Operations, Finance, etc. 

Data Orchestration builds and operates the time-based and event-based orchestration infrastructure that powers and accelerates batch data pipelines. The team operates on a wide range of tech stacks including Airflow, Spark, SQL, Kafka, Flink, Hive MetaStore, Trino, Pinot, Python, Java, Scala, S3, and Iceberg. 

What you’ll do 

As a Software Engineer on our team, you will do the following: 

• Design, build, and maintain innovative next-generation or first-generation versions of key Data Platform products, with an emphasis on usability, reliability, security, and efficiency. 
• Design ergonomic APIs and abstractions that build a great customer experience for internal Stripes, that will in turn enhance the experience of millions of Stripe users.
• Ensure operational excellence and enable a highly available & reliable Data Orchestration platform across batch workloads. 
• Collaborate nimbly with high-visibility teams and their stakeholders to support their key initiatives - while building a robust platform that benefits all of Stripe in the long term. 
• Plan for the growth of Stripe’s infrastructure by unblocking, supporting, and communicating proactively with internal partners to achieve results. ● Connect your work with improvements in the usability and reliability of Open Source Software (OSS) like Apache Airflow, Iceberg, Spark and contribute back to the OSS community. 

Who you are 

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. 

Minimum requirements 

• 8+ years of professional experience writing high quality production level code or software programs and interest in Data Infrastructure. 
• Has experience operating or enabling large-scale, high-availability data pipelines from design, to execution and safe change management. Expertise in Spark, Flink, Spark, Airflow, Python, Java, SQL, and API design is a plus. 
• Has experience developing, maintaining, and debugging distributed systems built with open source tools 
• Has experience building infrastructure-as-a-product with a strong focus on users needs 
• Has strong collaboration and communication skills, and can comfortably interact with both technical and non-technical participants. 
• Has the curiosity to continuously learn about new technologies and business processes. 
• Is energized by delivering effective, user-first solutions through creative problem-solving and collaboration. 

Preferred qualifications 

• Has experience writing production-level code in Expertise in Scala, Spark, Flink, Spark, Airflow, Python, Java, and SQL is a plus.
• Has experience designing APIs or building developer platforms ● Has experience optimizing the end to end performance of distributed systems ● Has experience with scaling distributed systems in a rapidly moving environment ● Has experience working with Airflow Infrastructure. 
• Genuine enjoyment of innovation and a deep interest in understanding how things work 

Office-assigned Stripes spend at least 50% of the time in a given month in their local office or with users. This hits a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility about how to do this in a way that makes sense for individuals and their teams. 

Office location - Bengaluru , KA, India 

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Before Stripe, every growing internet platform had a payments team. Today, every growing internet platform has an Identity team. Identity verification has become core economic infrastructure for online businesses — enabling them to digitally verify their users' identities for fraud prevention, regulatory compliance, and trust and safety purposes.

At Stripe, we're building something more ambitious than a verification product. Our vision is to build the world's most trusted store of verified identities — a single, global, reusable, risk-scored representation of every individual who interacts with Stripe and beyond. This Identity Store becomes a platform with compounding network effects: more verifications enrich the store; a richer store produces better fraud signals; better signals mean lower friction for trusted users; lower friction drives more adoption.

Our product today serves millions of verifications per month for customers like OpenAI, Shopify, and WhatNot, and powers identity verification across multiple internal Stripe products including Fraud, Link, Connect, and Crypto. The problems ahead — adversarial AI and deepfake defense, networked identity infrastructure, progressive verification platforms, and low friction KYC APIs — sit at the frontier of what's possible in identity engineering.

What you’ll do

As a Staff Engineer on the Identity team, you will own the technical direction of one of Stripe's most strategically important product areas. This is not a role defined by task execution — it's a role defined by technical judgment, architectural influence, and the ability to turn an ambitious vision into a reliable, scalable system.

Responsibilities

• Own technical strategy — Define the architecture for Identity's core systems (Identity Store, headless verification platform, fraud detection infrastructure), make build-vs-buy-vs-partner decisions, and surface technical risks before they become customer-facing failures
• Lead 0-1 platform development — Architect net-new systems including the Identity Store, Networked Identity platform, and advanced fraud detection pipeline (behavioral biometrics, deepfake discriminators, adversarial training). Drive the evolution from a hosted-UI product to a headless-API and embedded-components platform
• Drive cross-functional alignment — Be the primary technical voice in roadmap and resourcing discussions. Partner with ML, product, legal, and engineering leads across Risk, Fraud, Link, Connect, and Crypto to ensure Identity's abstractions serve the full breadth of Stripe's product surface
• Raise the technical bar — Set engineering standards across ML, backend, mobile, and front-end; lead design reviews; and mentor senior engineers on the judgment needed to operate a high-stakes, externally-facing product
• Operate with ownership — Be accountable for reliability, scalability, and security of the systems you design — including the observability and alerting that catch model drift and fraud pattern shifts before customers do

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 10+ years of software engineering experience, including 5+ years of experience in a strategic technical leadership role.
• Experience leading engineering team(s) working on API design, abstractions, frameworks, or client libraries (e.g. building internal or external developer products). 
• Proven track record of delivering pragmatic solutions that accelerate business growth 
• Ability to adjust conversations from high-level discussions to detailed coding 
• Thrives on a high level of autonomy and responsibility 
• Clear and persuasive writing and in-person communication 
• Strong problem-solving skills, critical thinking, determination, and a growth mindset 
• Ability to work effectively with a diverse group of people, genuinely caring for each other and contributing to high level of psychological safety for all team members and partner
• Has experience in a range of software languages and frameworks. Examples of what we work with include:
• Languages: primarily Ruby and Typescript, but also Python, Scala, Java, Go, and SQL (Spark and Trino dialects)
• Frameworks: React, GraphQL Kafka, Protobuf, Airflow, Bazel, Temporal, 
• Others: Mongo, Splunk, Prometheus

Preferred qualifications

• Experience with identity verification, fraud detection, or trust and safety systems — especially systems with adversarial inputs at scale
• Familiarity with ML systems in production: model serving, training pipelines, observability, drift detection, and the feedback loops that keep models accurate under adversarial conditions
• Experience building platform products with multiple consumer types — internal platform teams and external developers — where API backward compatibility and abstraction quality are first-class concerns
• Prior experience with 0-1 product builds: you've started with a blank page and ended with a production system, and you have clear opinions about what makes that process go well or poorly
• Exposure to the technical stack we work with: primarily Ruby and TypeScript on the backend and web, Python for ML and data pipelines, with infrastructure spanning Kafka, Temporal, Protobuf, React, and distributed data stores
• Experience navigating ambiguity in a fast-moving organization — you can make confident technical decisions with incomplete information and update gracefully when new constraints emerge

Why Stripe Identity

• The market is at an inflection point. The global identity verification market is growing at ~15% CAGR, from $12.5B in 2024 to $21.8B by 2028. Competitors have more features today — but none of them have Stripe's moat: payments signals, fraud network, consumer graph, and KYC data spanning the full financial ecosystem. We're building to win the next decade, not the last one.
• The problems are genuinely hard. Adversarial ML against deepfakes and face swaps. Distributed identity graph architecture with real-time freshness requirements. Progressive verification APIs that minimize friction without sacrificing fraud detection accuracy. These are unsolved problems — not just at Stripe, but in the industry.
• You'll work on systems that matter immediately. The verifications we run protect real users from real fraud. When our recall improves by 10 points, that's millions of dollars in prevented fraud losses for customers who rely on us. When our mobile SDK completion rate rises, thousands more legitimate users successfully onboard each month.
• The team is small enough that your judgment shapes the architecture. This isn't a role where you inherit decisions made five years ago. It's a role where the decisions you make in 2026 are the ones the team will build on through 2029.

Who We Are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the Team

The Batch Compute Infrastructure team at Stripe manages the foundational infrastructure, tooling, and distributed systems behind Stripe's massive-scale batch processing environments, currently encompassing over 5,000 computational nodes. Powered primarily by Hadoop, Spark, and Celeborn, these systems are the backbone for several core asynchronous financial, analytical, and regulatory workflows at Stripe, operating at petabyte scale.

What you’ll do -
You will support a team of engineers focused on building the tooling, infra and systems for operating Spark, Hadoop and Celeborn at Stripe. In addition to helping define the roadmap for these systems, you will be interacting with many other managers and their teams at Stripe, who rely on the Data processing Infra team to deliver efficient and scalable services to our customers. You will work with both the finance and engineering organization (infrastructure & product) to define, measure and monitor the cost efficiency of these systems. 

Responsibilities

• Drive Strategic Vision: Define the multi-year roadmap for Stripe’s Batch Compute Infrastructure, leading complex architectural shifts and modernization.
• Lead and Scale: Build, mentor, and aggressively scale a high-performing team of engineers, proactively investing in their career development and fostering a culture of operational excellence.
• Ensure Operational Rigor: Maintain unwavering reliability for a Tier-0 infrastructure processing tens of thousands of daily workloads, proactively mitigating risks and managing complex on-call telemetry.
• Cross-Functional Orchestration: Collaborate deeply with data platform teams, finance, and user groups to define compute efficiency metrics, execute massive-scale cost optimization strategies, and guarantee compliance with global financial regulations.
• Technical Stewardship: Provide technical guidance in architecture reviews, evaluating critical cost, performance, and reliability trade-offs in distributed systems design involving Hadoop, Spark, AWS cloud primitives, and modern metastores.

Who You Are

Minimum requirements

• 10+ years of professional software development and engineering experience.
• 3+ years of direct engineering management experience, successfully building and operating high-velocity technical teams.
• Deep technical background in building, scaling, and maintaining large-scale distributed data systems or Tier-0 infrastructure using open-source tools (e.g., Hadoop, Spark, Celeborn, Airflow, Kafka).
• Proven track record of driving significant infrastructure efficiency, managing capacity planning, and making data-driven cost-performance trade-offs.
• Experience working effectively in highly cross-functional, global organizations.

Preferred requirements

• Experience managing remote or geographically distributed engineering teams.
• Familiarity with managing a massive fleet of Linux servers, on-premise Hadoop clusters, and modern cloud data architectures (e.g., AWS S3, Graviton).
• Demonstrated ability to navigate strategic ambiguity and deliver complex, multi-quarter infrastructural projects from inception to completion.
• Deep empathy for internal data users with a passion for building robust developer tooling and abstractions.

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the team

Role Overview

We are seeking an analytically-driven Data Analyst to join our Finance & Strategy team at Stripe. This role bridges the gap between data science and financial planning, requiring someone who can transform complex business data into actionable financial insights. You will build sophisticated dashboards, develop predictive models, and serve as the technical backbone for our FP&A and GTM analytics initiatives. This is a unique opportunity for a data professional with financial acumen to directly influence strategic business decisions in a high-growth fintech environment.

What You'll Do

Financial Data Analytics & Modeling

• Design, build, and maintain financial dashboards for FP&A, Revenue Operations, and GTM teams using Tableau, Power BI, or Looker
• Develop automated financial reporting solutions that reduce manual effort and improve data accuracy
• Create sophisticated data models to support budgeting, forecasting, variance analysis, and scenario planning
• Build predictive models for revenue forecasting, customer lifetime value, churn analysis, and unit economics

Business Intelligence & Reporting

• Partner with Finance Business Partners and FP&A teams to translate business requirements into technical solutions
• Design and implement data infrastructure for financial planning cycles (monthly/quarterly reviews, annual budgets, long-range planning)
• Develop self-service analytics capabilities enabling finance teams to access real-time business insights
• Create executive dashboards tracking key financial and operational metrics (ARR, bookings, retention, CAC, LTV)

Data Engineering & Analytics Infrastructure

• Write complex SQL queries to extract, transform, and analyze large datasets from multiple source systems
• Build ETL pipelines to integrate financial data from ERP, CRM, billing, and data warehouse systems
• Ensure data quality, consistency, and governance across financial reporting systems
• Optimize database performance and data architecture for scalability

Strategic Analysis & Insights

• Conduct deep-dive analyses on business performance, identifying trends, anomalies, and opportunities
• Support strategic initiatives through ad-hoc financial modeling and what-if scenario analysis
• Translate complex data findings into clear, actionable recommendations for leadership
• Collaborate with Data Science teams to develop advanced analytics and ML models for finance use cases

Required Qualifications

Technical Skills

• Must Have: Advanced SQL proficiency (complex joins, window functions, CTEs, query optimization)
• Must Have: Expert-level experience with at least one BI tool (Tableau, Power BI, Looker, or Qlik)
• Must Have: Advanced Excel/Google Sheets skills (pivot tables, complex formulas, data modeling)
• Preferred: Python or R for data analysis, automation, and statistical modeling
• Preferred: Experience with cloud data platforms (Snowflake, BigQuery, Redshift, Databricks)
• Preferred: Knowledge of ETL tools (dbt, Airflow, Fivetran) and version control (Git)

Financial & Business Acumen

• Experience in data analytics within finance, FP&A, or revenue operations functions
• Strong understanding of financial statements (P&L, balance sheet, cash flow)
• Knowledge of key financial metrics: ARR, MRR, bookings, revenue recognition, CAC, LTV, gross margin, EBITDA
• Experience with financial planning processes: budgeting, forecasting, variance analysis, scenario modeling
• Understanding of SaaS/subscription business models and revenue recognition principles (ASC 606 preferred)

Analytical & Problem-Solving

• Proven ability to work with large, complex datasets and derive meaningful insights
• Experience building financial models and dashboards that drive executive decision-making
• Strong statistical analysis skills and understanding of data visualization best practices
• Track record of translating ambiguous business problems into structured analytical frameworks

Preferred Experience

• Background in fintech, payments, B2B SaaS, or high-growth technology companies
• Experience supporting GTM analytics (sales forecasting, pipeline analysis, quota setting)
• Familiarity with finance systems: NetSuite, Anaplan, Adaptive Planning, Salesforce, Stripe Billing
• Exposure to data science methodologies and machine learning concepts
• Previous work in cross-functional environments collaborating with finance, data science, and business teams

Key Competencies

• Business Acumen: Ability to understand complex business models and translate them into data requirements
• Technical Excellence: Deep technical skills with commitment to code quality and best practices
• Communication: Exceptional ability to explain technical concepts to non-technical stakeholders
• Stakeholder Management: Experience partnering with senior leaders and influencing through data
• Ownership Mindset: Self-directed with ability to manage multiple priorities and drive projects to completion
• Continuous Learning: Curiosity to learn new tools, techniques, and business domains
• Attention to Detail: Commitment to data accuracy and quality in high-stakes financial reporting

Education

• Bachelor's degree in Finance, Economics, Statistics, Mathematics, Computer Science, Engineering, or related quantitative field
• Advanced degree (MBA, MS in Analytics/Data Science) or relevant certifications (CFA, CPA, data analytics certifications) a plus

What Makes This Role Unique This position sits at the intersection of data engineering, business intelligence, and strategic finance. You'll have the autonomy to architect solutions that shape how Stripe makes multi-million dollar decisions, while working with cutting-edge data technologies and some of the brightest minds in fintech. If you're energized by the prospect of building the analytics infrastructure that powers a global payments platform, this role is for you.

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Web Presence and Platform is organized into two pillars, each of which is grouped into pods that focus on the central tenets of Stripe's public mission. The Presence pillar creates industry-leading designs for Stripe’s front door surfaces, educating customers about the power of our platform, sharing Stripe’s ideas and expertise with the public, and driving adoption. The Platform pillar builds the internal machinery that powers these surfaces, and is responsible for making our websites fast, stable, and easy to update.

Together we design and build stripe.com and other sites that amount to what is, for many, their first impression of Stripe. As such, WPP offers exciting opportunities to have a major impact on Stripe’s success. We want to make every pixel count, we want it to be enthralling, and we want to help other Stripes seamlessly benefit from our systematic work.

While the team's mission anchors to web surfaces, this role lives deeper in the stack. You will be the engine behind the experiences rather than the pixel-level presentation — APIs, data pipelines, model orchestration, and service reliability that make LLM-driven user experiences possible at scale.

What you’ll do

The Expansion pod brings creativity and executional rigor to attracting new prospects and driving conversion, focusing on user journeys, interactive and highly polished tools for users, and building targeted experiences for our global users.

As a backend engineer you will architect and build the server-side systems and LLM orchestration layers that power intelligent, dynamic user experiences across acquisition journeys. You will design the APIs, data pipelines, and inference infrastructure behind delightful and original interactive tools and resources that attract users. You will collaborate deeply across design, engineering, and cross-functional teams and work across teams and tech stacks to create new site capabilities — with a specific focus on integrating large language models into production-grade services that are reliable, performant, and safe.

This is not a research or ML training role. You will be responsible for wiring LLMs into real user-facing products: managing prompt pipelines, handling model routing and fallback logic, implementing guardrails and output validation.

Responsibilities

• Develop and implement the tooling and platforms to support interactive content tools (e.g., calculators, generators, templates) that provide utility to current and prospective businesses.
• Utilize a user-first mindset to implement feedback mechanisms for continuous improvement of content and product offerings.
• Design and build integrations to third-party software and create seamless workflows across these tools to unleash their full potential to the rest of Stripe.
• Ensure reliability, security, and responsible AI practices across all LLM-driven features, including implementing content filtering, PII handling, rate limiting, graceful degradation, and output guardrails.
• Work with a small team of technically sophisticated engineers who put users first.

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 5+ years of backend development experience, with emphasis on building APIs and services that power user-facing experiences
• Experience writing clear, elegant code in a team environment
• Familiarity with LLM APIs and concepts — prompt engineering, token management, embedding models, retrieval-augmented generation, or function calling. You don't need to be a researcher, but you should understand how these models work well enough to build production systems around them.

• Experience building and operating distributed backend systems — you're comfortable with service-oriented architectures, async processing, caching layers, and monitoring/alerting in production.
• Passion for engineering solutions focused around growth hacking & enablement 
• Excellent verbal and written communication

Preferred qualifications

• Proven ability to stitch different services and processes together even if you have not worked with them before
• Experience in developing interactive tools and integrating them with existing systems.
• Experience building highly complex interactive tools, including state management and data fetching
• Experience with data pipeline orchestration (Airflow, Dagster, Temporal, or similar) and structured output parsing from LLMs
• Experience with prompt versioning, A/B testing model outputs, or building model gateway/routing layers that allow teams to swap or compare providers (e.g., OpenAI, Anthropic, open-source models)
• Proficiency with React, with a focus on interactions, animation, performance, and polish
• Experience with A/B testing, synthetic monitoring, or accessibility testing

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

The Data Transformation team is responsible for building and operating batch and real time transformation pipelines and platforms for 400+ product teams at Stripe.  We're aiming to make data development and management workflow at Stripe a breeze with emphasis on producing high quality datasets used for critical analytics, dashboards and workflows at Stripe. The Products owned by this team are widely adopted with 800+ weekly active users improving developer productivity for data users by many folds. The team is in an interesting phase of innovation tied to topmost priority for Stripe building and executing the strategic roadmap for streaming transformation, incremental processing and ergonomic data modeling.    

We empower our users ranging from Data Scientists to Engineers building pipelines to create exceptional Stripe product experiences while providing a robust transformation platform for critical dashboarding, analytics and workflows at Stripe including user-facing reporting products Sigma and Radar. 

We adopt a combination of open source technologies and in-house built software to ensure high scalability, reliability, and usability of our transformation offerings. Key example technologies used include: Spark, Airflow, Iceberg, Hive, S3, SQL, Python, Scala, GRPC, Kafka and FlinkSQL.

What you’ll do

As an Engineering Manager of the Data Transformation team, you will lead a team of engineers, collaborate with infrastructure and product engineering orgs, and advance the Data Transformation roadmap and adoption at Stripe. You will be driving critical workstreams for Stripe’s topmost priorities around delivering high quality, materialized datasets Stripe products and AI agents.

You will:

• Deliver infrastructure and services that scale to our users needs with an eye on reliability and efficiency
• Lead and manage a team of talented engineers on the team, providing mentorship, guidance, and support to ensure their success
• Work with high-visibility teams and their stakeholders to support the Infrastructure’s key engineering initiatives
• Understand user needs and pain points to prioritize engineering work and deliver high quality solutions that meet user needs
• Drive the execution of projects, overseeing the entire development lifecycle from planning to delivery, while maintaining high standards of quality and timely completion
• Provide hands-on technical leadership (architecture/design, vision/direction/requirements setting, and incident response processes) for your reports
• Work with leaders across the company to create and drive toward the longer term vision of Stripe’s Data Transformation roadmap
• Foster a collaborative and inclusive work environment, promoting innovation, knowledge sharing, and continuous improvement within the team
• Partners with our recruiting team to attract and hire top talent, and define the overall hiring strategies for your team

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

We’re looking for someone who has: 

• 1 - 3 years of experience managing teams that shipped and operated data pipelines and critical distributed system infrastructure
• Successfully recruited and built great teams.
• Extreme customer focus, committed to investing in partnerships with other Stripe engineers to establish empathy and understand their use-cases
• Works effectively cross-functionally and is able to think rigorously, communicate effectively, and make or coordinate hard decisions and trade-offs.
• Thrives with a high degree of autonomy and responsibility in an ambiguous environment.
• Technical acumen to drive clarity with staff engineers about architecture and technical strategic decisions.
• Encourage a healthy and inclusive work environment that’s both challenging and supportive

Preferred qualifications

• Managed teams that shipped products to data users and operated large-scale, high-availability data transformation pipelines, with expertise in Kafka, Flink, Spark, Airflow, Python, SQL, and API design a plus.
• A genuine enjoyment of learning and diving into the nuts-and-bolts of how things work, with the ability to question and direct architectural decisions
• Strong written and verbal communication skills for different audiences (leadership, users, company-wide)

We deliver a connected healthcare experience for over a quarter million members and 60+ companies across the nation who want the best for their employees. We've got a ton of interesting problems to solve around data pipeline design and implementation, data architecture and modeling, distributed systems, and more. If you're passionate about tackling hard problems while making a real difference in the world, we'd love to talk!

What you'll do: 

• Data Infrastructure Orchestration - Build and maintain cloud native infrastructure for Data Platform (AWS, Terraform)
• Data Pipelines - Create new pipelines and improve/maintain existing pipelines using Spark (Python, Pyspark, SQL)
• Data Modeling - Partner with analytic consumers to design logical and physical schemas, improve existing data models and build new ones
• Cross-functional Collaboration - Interface with Product, Engineering, Data Science, Analytics/BI, and Operations to understand their data needs, providing both consultative and data engineering solutions for consumers
• Build data expertise and own data quality across various business domains including healthcare claims and member experience
• Manage the Business Intelligence development lifecycle, from semantic model development and version control to user administration, ensuring high data quality and consistency from the pipeline through to the visualization layer.
• Enable fellow developers to “self-service” their data needs
• Leverage best in industry practices to build the next generation data ecosystem to collect, move, store and analyze data

To be successful in this role, you'll need:

• BS degree in Computer Science or related technical field, or equivalent practical experience
• 4+ years proven work experience as a data engineer, working with at least one programming language (e.g. Scala, Python/PySpark) plus SQL expertise
• 4+ years experience with schema design, dimensional data modeling, and large-scale data warehousing architecture
• Expertise in building data pipelines through efficient ETL design, implementation and maintenance 
• Background working with distributed data systems such as Spark, Presto, Hive, and Redshift. Experience with BI platform administration and/or schedulers/workflow management tools (e.g. Airflow) a plus
• Excellent communication skills to collaborate with stakeholders in Engineering, Product, Data Science, Analytics/BI, and Operations

Pay Transparency Statement 

This is a hybrid position based out of our Plano office, with the expectation of being in office at least three weekdays per week. #LI-hybrid

The actual pay rate offered within the range will depend on factors including geographic location, qualifications, experience, and internal equity. In addition to the salary, you will be eligible for 115,000 stock options and benefits like health insurance, 401k, and paid time off. Learn more about our benefits at https://jobs.collectivehealth.com/benefits/.

About this role

As a Staff Machine Learning Platform Engineer, you will help design, improve, and operate a scalable ML platform to accelerate model training, deployment, and governance. You are the technical bridge between data science and production engineering.  You’ll be joining a small but deeply critical team that scales Faire’s ability to support tens of thousands of local businesses in a constantly narrowing retail landscape.

What You Will Do

• Design and operate ML infrastructure, including workspaces, clusters, jobs, and workflows
• Productionize ML workloads using Spark, Delta Lake, MLflow, and Databricks Workflows
• Teach data scientists how to utilize our ML platform to advance development from notebook to production for our most critical models
• Implement Unity Catalog for data governance, lineage, access control, and secure multi-tenant usage
• Build CI/CD pipelines for ML using Terraform and Git-based workflows (e.g., GitHub Actions)
• Optimize performance, reliability, and cost across training and inference workloads
• Configure Identity and Access Management (IAM) and Role Based Authentication Controls (RBAC) for sensitive data sets
• Establish observability for data quality, model performance, and platform health
• Build and maintain ML Platform technical documentation

What it takes

• 8+ years of experience building production ML or data platforms
• A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field
• Strong hands-on expertise with Databricks, Spark, Delta Lake, and MLflow.
• Proficiency in Python, SQL, and distributed systems concepts
• Experience with cloud platforms and infrastructure-as-code
• Solid understanding of MLOps best practices: CI/CD, monitoring, reproducibility, and security
• Experience supporting multiple ML teams in a shared platform environment
• Are an active owner of orphaned problems and are willing to assimilate whatever knowledge you’re missing to get the job done

Tech Stack

Faire uses a modern cloud based tech stack.  For this role, you’ll want to be proficient with the following:

Salary Range

Canada: the pay range for this role is $216,000 to $297,000 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

Data at Brex

The Data organization develops insights, models, and data infrastructure for teams across Brex, including Sales, Marketing, Product, Engineering, and Operations. Our Data Scientists, Analysts, and Engineers work together to make data—and insights derived from data—a core asset across the company.

What you’ll do

As a senior Data Analyst (DA III), you will own the end-to-end analytics lifecycle for one or more business areas at Brex. You’ll go beyond building dashboards—you’ll frame the right questions, design rigorous analyses, apply statistical methods, and translate your findings into clear recommendations for leadership. You will also serve as a technical leader on the Data Analytics team, mentoring more junior analysts and helping define the standards and best practices that elevate the team’s work.

This role sits at the intersection of analytics, analytics engineering, and business strategy. You’ll work in a modern data stack environment and partner closely with Data Scientists, Data Engineers, and senior leaders across the organization.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own the analytics lifecycle for assigned business areas: from problem framing and data sourcing through analysis, insight generation, and stakeholder presentation.
• Build and maintain dashboards and self-service reporting tools that enable business teams to independently track performance, identify risks, and make data-driven decisions.
• Write production-quality SQL and Python code to extract, transform, and analyze data at scale.
• Collaborate with Data Engineers and Data Scientists to develop and maintain analytical data models, improve data pipelines, and ensure data quality across the organization.
• Partner with leadership across Sales, Operations, Product, Finance, and other departments to identify high-impact analytical opportunities and deliver actionable recommendations.
• Mentor other data analysts and contribute to the development of team standards, documentation, code review practices, and analytical frameworks.
• Proactively identify gaps in data infrastructure, propose improvements, and contribute to the evolution of the team’s tooling and processes.

Requirements

• 5+ years of experience in data analytics, business intelligence, or a related quantitative role.
• 3+ years of experience partnering directly with Sales, Operations, Product, or equivalent business teams as an embedded analytics partner.
• Advanced SQL proficiency, including CTEs, window functions, performance optimization, and working across complex data models.
• Proficiency in Python for data analysis, automation, and modeling (Pandas, NumPy, scikit-learn, or similar).
• Experience with cloud data warehouses, particularly Snowflake (BigQuery and Databricks also valued).
• Hands-on experience with BI and data visualization tools (Looker, Tableau, Hex, or similar).
• Strong stakeholder management skills—proven ability to present complex technical findings to non-technical audiences.
• Experience with generative AI and LLM-based tools (Claude Code, Cursor, GitHub Copilot) to perform and accelerate analyses, automated reporting, and build self-service data tools.

Bonus points

• Demonstrated experience applying statistical methods to business problems (e.g., regression, classification, A/B testing).
• Experience with dbt for data modeling and transformation.
• Experience building and maintaining data pipelines using orchestration tools such as Airflow.
• Experience working with APIs for data ingestion and integration.
• Familiarity with version control systems (Git).
• Experience in fintech, financial services, or payments.
• Track record of leading cross-functional analytics projects from scoping through delivery.

Compensation

The expected salary range for this role is $114,192 - $142,740. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Data at Brex

Our Scientists and Engineers work together to make data — and insights derived from data — a core asset across Brex. But it's more than just crunching numbers. The Data team at Brex develops infrastructure, statistical models, and products using data. Our work is ingrained in Brex's decision-making process, the efficiency of our operations, our risk management policies, and the unparalleled experience we provide our customers.

What You’ll Do

As a Data Engineer at Brex, you will be a core contributor in transforming raw data into actionable insights for various departments across the organization. You'll collaborate closely with Data Scientists, Software Engineers, and business units to create efficient data models, pipelines, and analytics frameworks that drive the business forward. You also play a leading role in the design, implementation, and maintenance of Core Data tables, our high-quality, curated data source for a wide range of analytic applications. 

Where you’ll work

This role will be based in our Sao Paulo office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities:

• Design, build, and maintain data models and pipelines that scale with the growing number of services, products, and changes in the company.
• Collaborate closely with Data Scientists, Data Analysts, and Business teams to understand their data needs, translating them into robust, efficient, scalable data solutions that enable ease of predictive analytics, data analysis, and metrics formulation. 
• Maintain data documentation and definitions, building and ensuring that source-of-truth tables remain high quality for data science and reporting applications. 
• Develop and enable integration with various data sources, allowing for more data-driven initiatives across the company.
• Apply best practices in data management to ensure the reliability and robustness of data utilized across various analytics applications.
• Set and proliferate company-wide standards for data relating to structure, quality, and expectations.
• Act as a liaison between the technical and non-technical teams, bridging gaps and ensuring that data solutions align with business objectives.
• Use agentic AI where it speeds up pipeline and quality work, without skipping validation.

Requirements:

• 3+ years of experience in Data Engineering, Data Analytics, or a related field such as Analytics Engineering.
• Advanced knowledge of databases and SQL with the ability to efficiently stage, process, and transform data.
• Experience integrating and orchestrating data workflows with various modern data tools and systems.
• Experience with data modeling, ETL/ELT processes, and data warehousing solutions.
• Experience working with a data warehouse such as Snowflake.
• Experience with a data workflow orchestrator tool such as Airflow.
• Experience with a programming language such as Python. 
• Experience with agentic AI. 
• Exceptional quantitative and analytical skills.
• Strong communication skills and ability to collaborate with various stakeholders, both technical and non-technical.

Nice to have:

• Familiarity with BI tools such as Looker, Tableau, or similar platforms. 
• Solid dbt in production: models, tests, docs, and collaboration in a shared repo. 
• AI-ready data: Metrics and dimensions are clear and reusable so AI-assisted analysis does not fork definitions. 
• Experience with Salesforce data integration. 

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Data at Brex

Our Scientists and Engineers work together to make data — and insights derived from data — a core asset across Brex. But it's more than just crunching numbers. The Data team at Brex develops infrastructure, statistical models, and products using data. Our work is ingrained in Brex's decision-making process, the efficiency of our operations, our risk management policies, and the unparalleled experience we provide our customers.

What You’ll Do

As a Data Engineer at Brex, you will be a core contributor in transforming raw data into actionable insights for various departments across the organization. You'll collaborate closely with Data Scientists, Software Engineers, and business units to create efficient data models, pipelines, and analytics frameworks that drive the business forward. You also play a leading role in the design, implementation, and maintenance of Core Data tables, our high-quality, curated data source for a wide range of analytic applications. 

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities:

• Design, build, and maintain data models and pipelines that scale with the growing number of services, products, and changes in the company.
• Collaborate closely with Data Scientists, Data Analysts, and Business teams to understand their data needs, translating them into robust, efficient, scalable data solutions that enable ease of predictive analytics, data analysis, and metrics formulation. 
• Maintain data documentation and definitions, building and ensuring that source-of-truth tables remain high quality for data science and reporting applications. 
• Develop and enable integration with various data sources, allowing for more data-driven initiatives across the company.
• Apply best practices in data management to ensure the reliability and robustness of data utilized across various analytics applications.
• Set and proliferate company-wide standards for data relating to structure, quality, and expectations.
• Act as a liaison between the technical and non-technical teams, bridging gaps and ensuring that data solutions align with business objectives.
• Use agentic AI where it speeds up pipeline and quality work, without skipping validation.

Requirements:

• 3+ years of experience in Data Engineering, Data Analytics, or a related field such as Analytics Engineering.
• Advanced knowledge of databases and SQL with the ability to efficiently stage, process, and transform data.
• Experience integrating and orchestrating data workflows with various modern data tools and systems.
• Experience with data modeling, ETL/ELT processes, and data warehousing solutions.
• Experience working with a data warehouse such as Snowflake.
• Experience with a data workflow orchestrator tool such as Airflow.
• Experience with a programming language such as Python. 
• Experience with agentic AI. 
• Exceptional quantitative and analytical skills.
• Strong communication skills and ability to collaborate with various stakeholders, both technical and non-technical.

Nice to have:

• Familiarity with BI tools such as Looker, Tableau, or similar platforms. 
• Solid dbt in production: models, tests, docs, and collaboration in a shared repo. 
• AI-ready data: Metrics and dimensions are clear and reusable so AI-assisted analysis does not fork definitions. 
• Experience with Salesforce data integration. 

Compensation:

The expected salary range for this role is $120,800 - $151,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

WE’RE HIRING! If you love data and are looking for unlimited growth opportunities, we want to talk with you about joining Further.

Further is a data, cloud, and AI company whose focus is helping companies turn raw data into the right decisions. We have an award winning culture of extraordinary people. Our purpose is to enable people to thrive so that businesses can thrive. We believe that the work you do should matter - it should be meaningful to you professionally and personally, and it should have a positive impact on both you and our clients.  If this sounds exciting to you, let’s chat!

Data Architect

You own the data spine of the platform: the canonical event envelope, the multi-tenant transactional store, the read-side projections that power every console view and API response, and the AI/ML data infrastructure that makes the system intelligent rather than just instrumented. This is not a specialist role. We are hiring one person who has done all three surfaces at production depth and can hold the trade-offs simultaneously. The data volume is significant, the schema evolution problem is hard, the tenant isolation requirements are unforgiving, and the AI workloads sit on top of all of it. If any of those three surfaces feel uninteresting, this isn't the role. You'll work shoulder-to-shoulder with the Solution Architect on the canonical data model and with the Senior Developer on implementation. You write the migration playbooks, the upcaster chains, the projection rebuild procedures, and the runbooks that let us sleep at night. You will sit in our headquarters in Dallas, TX on a hybrid schedule. The team is in office on Tuesdays, Wednesdays and Thursdays. 

What experience should you have:

• 10+ years of data engineering, data platform, or database architecture experience, with at least 3 owning the architecture, not just the implementation.
• Production experience with event-sourced systems. You have personally implemented or evolved an event envelope, dealt with the upcaster chain problem, and lived with the consequences of an early schema decision.
• Deep Postgres expertise: schema design, indexing, query plan analysis, RLS. Not "I've used Postgres" but "I know what I'd do differently from the last team."
• Experience with streaming platforms: Kafka, Redpanda, Pulsar, or Kinesis. You understand the difference between a topic, a partition, a consumer group, and a saga, and you've designed for all of them.
• Production analytical data infrastructure experience: warehouse design (Snowflake, BigQuery, Databricks, ClickHouse) or modern OLAP patterns. You can take an event log and produce a queryable shape that analysts and AI systems can actually use.
• Hands-on AI/ML data infrastructure experience: vector databases (pgvector, Pinecone, Weaviate, Qdrant), embedding pipelines, retrieval patterns. You have shipped a RAG system that worked and you know why most of them don't.
• Strong SQL, strong enough to be the person other engineers go to.

Nice to have

• Drizzle, Prisma, or another modern TypeScript ORM at production depth.
• Workflow engine experience (Temporal, Cadence, Airflow) and the data implications of long-running processes.
• Background in feature stores, ML pipelines, or model evaluation infrastructure.
• Semantic layer experience: dbt, Cube, or Malloy.
• Compliance experience: SOC 2, HIPAA, GDPR, data residency. The audit story is part of the data story.
• Open-source work or public writing on data architecture.

What you’ll be doing in this role:

• The canonical event envelope and schema evolution strategy: how events are versioned, how upcasters chain, how projections rebuild, and how we add fields without breaking history. You write the rules and enforce them in code review.
• The transactional data layer: Postgres schema design, tenant isolation via row-level security, indexing strategy, query patterns, and migration discipline. Every table in a data plane carries a tenant_id and a policy. You make sure of that.
• The read-side architecture: projection design, materialized views, semantic layer for downstream analytics and AI consumption. You decide how we move from event log to queryable shape and how that shape stays cheap to maintain.
• The AI/ML data infrastructure: vector stores, embedding pipelines, retrieval-augmented generation patterns, feature stores where applicable, and the lineage that lets us trust what comes back.
• Data governance: lineage, retention, deletion (right-to-be-forgotten in a multi-tenant event-sourced system is a real problem and you'll solve it), and the audit story for every piece of customer data we touch.
• The operational playbook: projection rebuilds, replay procedures, schema migrations on hot data, vector index maintenance, capacity planning. If the data layer goes sideways at 2am, your runbook is what saves the on-call engineer

Our total rewards program is designed for your protection, peace of mind, and overall well-being. In addition to our outstanding basics, we offer a net-zero cost medical option, company contributions to your HSA, fertility support, fully-paid parental leave, a monthly stipend for your lifestyle spending account, and much more.

Apply today or check out all our opportunities!

#LI-Hybrid

Applicants must be currently authorized to work in the United States on a full-time basis. The company does not anticipate providing sponsorship for employment visa status (e.g., H-1B, TN, etc.) for this individual position.

Staff PRODUCT ENGINEER (Contract)

Build it. Ship it. Own it.

Location: Argentina, Brazil, Colombia, Chile, Mexico, Dominican Republic, Peru

About Counterpart

Counterpart is an insurtech platform reimagining management and professional liability for the modern workplace. We believe that when businesses lead with clarity and confidence, they become more resilient, more innovative, and better prepared for what's ahead. That's why we built the first Agentic Insurance™ system — where advanced AI and deep insurance expertise come together to proactively assess, mitigate, and manage risk. Backed by A-rated carriers and trusted by brokers nationwide, our platform helps small businesses grow with confidence. Join us in shaping a smarter future, helping businesses Do More With Less Risk®.

The Role

As a Product Engineer at Counterpart, you own problems and drive outcomes. You iron out requirements with stakeholders, partners, and customers. You leverage AI for implementation. You verify the end-to-end result. You iterate until you move the needle.

You run projects with other Product Engineers and AI agents. You know when to delegate to a human, when to delegate to an agent, and when to do it yourself. 

YOU WILL

Own the Problem

• Take accountability for the outcome. 
• Talk directly to your users, stakeholders, and peers to discover the problem. 
• Translate business intents into functional requirements that engineers and agents can build against. Determine where human judgment is non-negotiable and where AI can augment or act autonomously. 
• Own the non-functional technical requirements. Specify the quality bar: performance, scalability, reliability, security, maintainability.

Build with AI

• Write production-quality code across the stack: Python, Django, AWS, React, and PostgreSQL. You are not afraid of any layer.
• Direct agents and review their output with domain depth. Catch what they miss across the functional and non-functional bar: correctness, edge cases, performance, security, testability, readability.
• Evaluate and improve agent output regularly. Track failure modes. Refine the prompts and patterns that lift the quality ceiling over time.
• Run projects that span other Product Engineers and agents. Coordinate work, manage dependencies, and keep things moving without micromanaging.
• Contribute to architectural decisions. Bring options and alternatives, not objections. Know when the elegant solution is the wrong call for a startup moving fast.
• Contribute to and manage the context harness as you build and deliver.

Verify and Iterate

• Surface delivery risks early. Bring solutions, not just problems. Keep your stakeholders informed without turning every risk into a meeting.
• Verify the end-to-end result yourself. Confirm the system does what the requirements say, and that the requirements were right.
• Drive adoption of what you ship. Documentation, enablement, and usage monitoring are part of the job.
• Monitor your services in production. Own the signal. Debug and fix what breaks.
• Participate in support rotations. When users run into issues with what you shipped, you investigate and fix them.
• Iterate until you move the needle. Shipping is not the finish line. Outcome is.

Raise the Bar

• Mentor engineers around you. Give direct, useful feedback. Leave things better than you found them.
• Make deliberate calls on technical debt: when to accumulate it, when to pay it down, when to refactor. Translate trade-offs into language that business leaders can act on.
• Operate to the engineering standards for quality, reliability, and operational excellence.

YOU HAVE

• 10+ years building production web applications across the full stack. The years are the floor, not the bar. What matters is whether you have actually done this: owned a problem end-to-end, written the spec, built the thing, coordinated the work, and shipped it without someone else holding the thread.
• Demonstrated experience gathering requirements directly. You have interviewed users, customers, and partner teams, and turned ambiguous intent into specs that engineers and agents can build against.
• Demonstrated experience owning both functional and non-functional requirements. You have defined what a system must do and held the line on how well it must do it.
• A track record of owning a domain or initiative without close supervision. You have navigated ambiguity, made judgment calls, and been accountable for the outcome.
• Extreme ownership and a bias for action. You do not sit and wait. You chase stakeholders, customers, and answers when you need them.
• Experience coordinating across engineers and AI agents on a shared initiative. You have managed the work without holding a formal management title.
• Strong technical judgment and the depth to catch what AI-generated code gets wrong: not syntax, but correctness, architecture, intent.
• Proficiency with Python and Django. Working knowledge of TypeScript, React, and PostgreSQL.
• Proficiency in developing with AI tools (Claude Code, Cursor, OpenAI Codex, similar) and the drive to stay ahead of how AI development practices are evolving.
• Domain curiosity. You learn the business context your work supports, not just the systems. You understand why the problem matters, not just how to solve it.
• The ability to communicate clearly across engineering, product, and business, translating technical complexity without losing meaning.
• Low ego and high Emotional Quotient (EQ). You influence without authority, take feedback well, and leave your ego out of technical decisions.
• Experience working with distributed, remote teams.

HOW THIS ROLE WORKS

Product Engineering exists to collapse the distance between a problem and a working solution. You own a problem or part of a vision. You shape it with stakeholders. You build it with AI. You verify it end-to-end. You iterate until the metric moves.

You work within the Context Architecture, a shared system of documentation, design patterns, and domain knowledge that gives you the technical context to make autonomous decisions at every step.

This is not a role for engineers who need to be told how. It is a role for engineers who can take a problem, fill in the gaps with good judgment, and ship something that works.

WHO YOU WILL WORK WITH

• Derrick Franco, Principal Engineer: After teaching himself to code at 13, Derrick went on to co-found Jumpstart in addition to building out the technical divisions at InvestorsAlley and Phinaz Media Group. Nowadays Derrick spends his time reading, with his wife, and working on his podcast The Future of Work Project.
• Julian Prokay, Principal Engineer: A veteran of the SaaS space with experience working on both student systems and construction management software. In his free time, he enjoys history podcasts and fantasy literature.
• Tony Nguyen, Engineering Manager: Tony is an engineering and platform leader with 25+ years of leadership experience at companies like Sony PlayStation Network, Intuit TurboTax, and ServiceNow. He thrives at building products, scaling teams, and leading organizations, but more so building people. He believes the best leadership and engineering comes from bringing your full identity to work. For him that's faith, family, and sports! Outside of work, you can catch him on the couch with his 3 adult children watching anime, going to Disneyland, or having game nights.
• Ron Alexessen, Engineering Manager: With experience at Hewlett-Packard, New Relic, Rackspace, and consulting agencies, Ron has built teams and shaped technical culture across different environments. He's passionate about AI-enabled development as a force multiplier and building solutions that create real business impact. Outside work, he boulders, runs, rides gravel bikes, and co-parents active teenagers, embracing structured chaos in all of it.
• Newton Truong, Engineering Manager: Newton joins Counterpart with 7+ years of experience in platform and data engineering. In his last company Thrive Market, he had a hand in building out new microservices and architecting data pipelines with Airflow and Spark. He's vegetarian and loves trying new restaurants when traveling. Nowadays he's busy keeping up with his 2-year-old and doing outdoor activities with his family.
• John Mendez, Engineering Manager: John has experience working at companies of all sizes. He enjoys startups and small-to-medium businesses, where he can wear multiple hats and help deliver solutions. Outside of work, he stays busy with his four kids and their activities. He also makes time to stay active by working out at home and running or walking with his dog.

COUNTERPART'S VALUES

• Conjoin Expectations - it is the cornerstone of autonomy. Ensure you are aware of what is expected of you and clearly articulate what you expect of others.
• Speak Boldly & Honestly - the only failure is not learning from mistakes. Don't cheat yourself and your colleagues of the feedback needed when expectations aren't being met.
• Be Entrepreneurial - control your own destiny. Embrace action over perfection while navigating any obstacles that stand in the way of your ultimate goal. Leverage AI ruthlessly. We measure success by outcomes, not lines of code written. Use every available AI tool to ship faster and think more strategically.
• Practice Omotenashi ("selfless hospitality") - trust will follow. Consider every interaction with internal and external partners an opportunity to develop trust by going above and beyond what is expected.
• Hold Nothing As Sacred - create routines but modify them routinely. Take the time to reflect on where the business is today, where it needs to go, and what you have to change in order to get there.
• Prioritize Wellness - some things should never be sacrificed. We create an environment that stretches everyone to grow and improve, which is fulfilling, but is only one part of a meaningful life.

WE OFFER

1. Work from Anywhere - Counterpart is a fully distributed company, meaning there is no office. We allow employees to work from wherever they do their best work, of course prioritizing meetings that often happen in US time zones.
2. Language Classes - We sponsor up to $100 per calendar year to be used towards language classes to help support your English language skills.
3. Paid Vacation and Time Off
4. Parental Leave - Development Partners will be eligible for unpaid Parental Leave to bond with a newborn, newly-adopted, or newly placed child. Under this policy, development partners and independent contractors will be eligible for up to 8 weeks of unpaid parental leave. Any time off will be subject to approval and must be requested at least 45 days in advance.
5. Computer - We reimburse you for your locally procured MacBook Pro. If you are still with the company after one year, it is yours to keep!

Our estimated pay range for this role is USD $90,000 - $110,000 annually. Contractor compensation is determined by a variety of factors, including but not limited to, market data, location, internal equitability, and experience.

We are committed to being a welcoming and inclusive workplace for everyone, and we are intentional about making sure people feel respected, supported and connected at work, regardless of who you are or where you come from. We value and celebrate our differences and we believe being open about who we are allows us to do the best work of our lives.

We are an Equal Opportunity Employer. We do not discriminate against qualified applicants or employees on the basis of race, color, religion, gender identity, sex, sexual preference, sexual identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, military status, or any other characteristic protected by federal, state, or local law, rule, or regulation.