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

Come Work With Us:

Metropolitan Commercial Bank (“MCB” or the “Bank”) is a New York City–based, full-service commercial bank providing tailored banking solutions to businesses, institutions, and individuals. Founded in 1999, MCB operates banking centers in Manhattan and Boro Park, Brooklyn, within New York City, as well as in Great Neck on Long Island, New York, and Lakewood, New Jersey. The Bank recently expanded to Miami, Florida with their newest Brickell banking center.

Metropolitan Commercial Bank offers a comprehensive suite of commercial, business, and personal banking products and services to small businesses, middle-market and corporate enterprises, private and public institutions, municipalities, and local government entities.

The Bank has earned national recognition for its financial performance, innovation, and strategic growth. The Bank was named one of Newsweek’s Best Regional Banks in 2024 and 2025. Additionally, MCB recently received Editor’s Choice recognition at the Banking Tech Awards USA for Digital Onboarding & Omnichannel Banking and in 2026, the Bank earned Great Place To Work certification and received the Web Award Standard of Excellence for MCBankNY.com.

We are a client-focused organization that values technological innovation and excellence. A strong technical mindset, AI fluency, and adaptive skills are essential for our employees to effectively contribute to our mission and drive our success. We foster human–AI teaming and strong governance to ensure technology is used responsibly and in alignment with Bank policies and procedures. For more information about the Bank, please visit the Bank’s website at MCBankNY.com.

Position Summary:

Metropolitan Commercial Bank (the “Bank”) is seeking a VP-level AI/ML Engineer to deploy AI solutions at enterprise scale, with a strong emphasis on Large Language Model (LLM) applications and modern MLOps & AIOps practices. This role sits at the intersection of data science and software engineering, reporting to the manager of the IT Application Development and Support team and working closely with the Chief Artificial Intelligence Officer, transforming innovative AI prototypes into robust, scalable production systems. The AI/ML Engineer will lead the deployment of high-impact AI capabilities (e.g., generative AI systems, personalization engines, automation tools) and ensure scalable AI platforms that deliver real-world value. The role also includes designing, constructing, and maintaining the Bank’s AIOps solution, with Snowflake as the primary ML platform (e.g., Snowpark Python, UDFs/UDTFs, Tasks/Streams, and Snowflake-native ML).

Standard 4-day in-office requirement, 1 day remote (of your choosing)

Essential Functions & Responsibilities 

Production Architecture & AIOps

• Establish and enforce architecture standards for production AI systems, including data pipelines, model serving infrastructure, and real-time inference services.
• Implement AIOps/MLOps pipelines for CI/CD of ML models, model governance, monitoring, and lifecycle management.
• Design and maintain scalable software applications with integrated AI/ML capabilities.
• Develop software architecture and design patterns to ensure performance and scalability.
• Write clean, maintainable code in general-purpose programming languages (Python, Java, C, C++, Go).
• Implement and manage data pipelines for preprocessing and transforming data for AI/ML models.
• Integrate AI/ML models into production environments and optimize for reliability and scalability.
• Apply Site Reliability Engineering (SRE) principles and implement monitoring and alerting solutions.
• Conduct code reviews and provide technical guidance to junior developers.
• Stay current with advancements in software engineering and AI/ML technologies.
• Adhere to agile and lean software development best practices.
• Thoroughly document all developed models and processes according to relevant policies and standards.
• Support the production environment by either resolving technical or functional issues, in line with the procedures defined by the Bank.

Cross-Functional Collaboration

• Partner with data scientists, AI scientists, product managers, data engineers, DevOps, and business stakeholders to operationalize AI algorithms.
• Mentor or train teams and coordinate between research-oriented AI scientists and engineering teams to continuously improve models with production feedback.

Scaling & Performance

• Ensure AI solutions perform at scale, handling thousands of daily inferences with low latency and high reliability.
• Optimize model serving using techniques like model compression, caching, and hardware acceleration.

Implement robust monitoring and alerting for model performance to detect and address degradation (e.g., drift, latency issues).

Qualifications & Skills:

• 6+ years of experience
• Master’s or PhD in a relevant field (Computer Science, Software Engineering,  Machine Learning, Data Science, Statistics, etc.) is strongly preferred, especially with research or thesis work related to AI/ML
• LLM & GenAI Mastery: Expert in building and deploying LLM-based applications using RAG, prompt engineering, and vector databases. Skilled in LLMOps tools (LangChain, LlamaIndex) and fine-tuning models for enterprise use, including agent-based architectures.
• MLOps & Cloud Infrastructure: Proficient in cloud ML platforms (AWS, GCP, Azure) and MLOps workflows. Uses Docker, Kubernetes, and IaC tools (Terraform, CloudFormation) for scalable deployments. Experienced in CI/CD, real-time inference, GPU optimization, and ML observability (Prometheus, Grafana, MLflow).
• Full-Stack Development: Capable of building end-to-end AI solutions, from front-end (React) to back-end APIs (Flask, FastAPI, Node.js). Skilled in integrating ML models with databases (SQL, NoSQL) and delivering seamless user experiences through robust software engineering.
• Proficient in Python (pandas, scikit-learn), deep learning (PyTorch/TensorFlow/Keras), NLP/LLMs, LangChain, embeddings/vector search, and classic ML.
• Experienced with Snowflake-native ML (Snowpark Python, UDFs/UDTFs, Tasks/Streams).
• Competent in data engineering (SQL, ETL/pipelines, Spark/PySpark) and handling large structured/unstructured datasets.
• Strong understanding of AI/ML algorithms, application architecture, and design patterns.
• Excellent problem-solving, analytical, communication, and collaboration skills.

Preferred Qualifications & Skills

• Financial services domain experience (fraud risk, AML, underwriting, or commercial/treasury analytics).
• Hands-on experience with Snowflake ML/Snowpark (Python), Tasks/Streams, secure external functions, and feature management/registry tooling.
• Familiarity with fairness toolkits, XAI frameworks, and preparing models for validation, audit, or regulatory exams.
• Knowledge of SR 23‑4 (third‑party risk), NYC Local Law 144 (AEDT), NYDFS Part 500 (cyber).
• Ability to work in a constantly evolving environment.
• Excellent written and verbal communication skills.
• Strong listening and teaching abilities.
• Demonstrated analytical, troubleshooting, and problem-solving skills.
• Quick learner of new technologies.
• Self-directed with strong technology and communication skills.
• Ability to synthesize multiple sources of information and understand the broader operational context of the Bank.
• Collaborative team player with a practical and creative approach in a dynamic work environment.
• Ability to handle ambiguity, multitask, and adapt quickly to changing priorities.

Potential Salary: $130,000 - $200,000 annually

This salary range reflects base wages and does not include benefits, bonus, or incentive pay. Salary bands are purposefully wide ranging to encompass the different factors considered in determining where a candidate falls in the range, including but not limited to, seniority, performance, experience, education, and any other legitimate, non-discriminatory factor permitted by law. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed here.

Metropolitan Commercial Bank provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

See yourself at Twilio

Join the team as Twilio’s next Staff Machine Learning Engineer.

About the job

This position is needed to scope, design, and deploy machine learning systems into the real world, the individual will closely partner with Product & Engineering teams to execute the roadmap for Twilio’s AI/ML products and services.

You will understand customers need, build data products that works at a global scale and own end-to-end execution of large scale ML solutions. 

To thrive in this role, you must have a deep background in ML engineering, and a consistent track record of solving data & machine-learning problems at scale. You are a self-starter, embody a growth attitude, and collaborate effectively across organizations.

Responsibilities

In this role, you’ll:

• Build and maintain scalable machine learning solutions in production
• Train and validate both deep learning-based and statistical-based models considering use-case, complexity, performance, and robustness
• Demonstrate end-to-end understanding of applications and develop a deep understanding of the “why” behind our models & systems
• Partner with product managers, tech leads, and stakeholders to analyze business problems, clarify requirements and define the scope of the systems needed
• Work closely with data platform teams to build robust scalable batch and realtime data pipelines
• Collaborate with software engineers, build tools to enhance productivity and to ship and maintain ML models
• Drive high engineering standards on the team through mentoring and knowledge sharing
• Uphold engineering best practices around code reviews, automated testing and monitoring

Qualifications 

Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

Required:

• 7+ years of applied ML experience with proficiency in Python
• Strong background in the foundations of Machine Learning and building blocks of modern Deep Learning
• Track record of building, shipping and maintaining Machine Learning models in production in an ambiguous and fast paced environment.
• Track record of designing and architecting large scale experiments and analysis to inform product roadmap.
• You have a clear understanding of frameworks like - PyTorch, TensorFlow, or Keras, why and how these frameworks do what they do
• Familiarity with ML Ops concepts related to testing and maintaining models in production such as testing, retraining, and monitoring.
• Demonstrated ability to ramp up, understand, and operate effectively in new application / business domains.
• You’ve explored modern data storage, messaging, and processing tools (Kafka, Apache Spark, Hadoop, Presto, DynamoDB etc.) and demonstrated experience designing and coding in big-data components such as DynamoDB or similar
• Experience working in an agile team environment with changing priorities
• Experience of working on AWS

Desired:

• Experience with Large Language Models

Location

This role will be remote, and based in India

Travel

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.

What We Offer

Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

HPC & Cloud Infrastructure Engineer

Important Information

Location: Singapore

12 months contract

Job Summary

We’re hiring an HPC & Cloud Infrastructure Engineer to design, deploy, and optimize high-performance computing environments across on-prem and cloud. You’ll manage HPC clusters, interconnects, job schedulers, and enable AI/ML workloads at scale while driving automation and cost efficiency

Job Description

Architect, deploy, and manage HPC clusters with job schedulers, parallel file systems, and cluster management tools

Design, configure, and troubleshoot Infiniband high-throughput, low-latency interconnects for HPC/distributed workloads

Own PBS Professional scheduling: deployment, queue optimization, custom job submission scripts, workload management

Administer RHEL-based systems: performance tuning, package management, security hardening, patching via Red Hat Satellite and Ansible

Build and maintain cloud HPC environments on AWS, Azure, and GCP – provisioning, hybrid setups, migrations, and cost optimization

Implement Infrastructure as Code using Terraform/Ansible and integrate with CI/CD pipelines for reproducible infrastructure

Enable GPU & AI/ML workloads: containers, TensorFlow, PyTorch, scikit-learn, Keras, MXNet; support MLOps pipelines for training and deployment

Optimize parallel applications using MPI and OpenMP; debug and scale distributed/shared memory workloads

Drive monitoring, logging, and alerting for cluster health, job efficiency, and resource utilization

Required Skills and Experience

High-Performance Computing

Hands on experience in managing HPC clusters with job scheduler, cluster management parallel programming libraries, and parallel filesystems.

Knowledge of resource scheduling and job optimization for efficient workload management

Infiniband (Networking)

Hands-on experience with high-throughput, low-latency interconnect technologies like Infiniband.

Ability to design, configure, and troubleshoot interconnects in HPC or distributed environments.

Operating Systems and Environments 

Administration and configuration of RHEL-based systems.

Performance tuning, package management, and security hardening.

Knowledge of Red Hat Satellite and Ansible for automation.

Job Scheduling with PBS Professional 

Experience in deploying and managing PBS Professional for scheduling and workload management in HPC environments.

Customizing job submission scripts and optimizing job queues.

Parallel Programming Libraries

MPI (Message Passing Interface) and OpenMP (Open Multi-Processing):

Proficiency in writing, debugging, and optimizing parallelized code.

Experience with scaling applications across HPC systems.

Understanding of distributed memory (MPI) and shared memory (OpenMP)

paradigms.

Cloud Platforms

AWS, Azure, Google Cloud:

Expertise in provisioning, configuring, and managing services on all three platforms.

Cross-platform migration and hybrid cloud solutions knowledge.

Proficiency in managing high-performance computing (HPC) clusters on the cloud.

Deep understanding of cost optimization, security, and cloud native development tools (e.g., Kubernetes, Terraform).

Infrastructure as Code (IaC) 

Ability to design, deploy, and maintain infrastructure using automation and configuration management tools.

CI/CD pipeline integration for IaC workflows.

GPU & AI Libraries and Tools 

Hands-on experience with container technologies.

Hands-on experience with TensorFlow, PyTorch, scikit-learn, Keras, or MXNet.

Familiarity with AI/ML pipelines, model training, and optimization.

Knowledge of MLOps tools for deploying and monitoring models

About Encora

Encora is a global company that offers Software and Digital Engineering solutions. Our practices include Cloud Services, Product Engineering & Application Modernization, Data & Analytics, Digital Experience & Design Services, DevSecOps, Cybersecurity, Quality Engineering, AI & LLM Engineering, among others.

At Encora, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.

Recent Projects For This Role Include

What You'll Do

• C++ - writing clean, modular, C++ code
• Traditional computer vision algorithms
• Training deep learning networks using TensorFlow, Keras, or similar
• Data structures and architecture
• Must be willing and able to work onsite five days per week

What You Bring

• Bachelor's Degree in Computer Science, preferably with research experience 
• 2+ years of industry software engineering experience
• 1+ years of work or research experience with current neural net frameworks
• Mastery of at least one practical programming language
• Experience working in a agile team software development environment

US Employee Benefits

Verkada is committed to fostering a workplace environment that prioritizes the holistic health and wellbeing of our employees and their families by offering comprehensive wellness perks, benefits, and resources. Our benefits and perks programs include, but are not limited to:

• Healthcare programs that can be tailored to meet the personal health and financial well-being needs - Premiums are 100% covered for the employee under at least one plan and 80% for family premiums under all plans
• Nationwide medical, vision and dental coverage
• Health Saving Account (HSA) with annual employer contributions and Flexible Spending Account (FSA) with tax saving options
• Expanded mental health support
• Paid parental leave policy & fertility benefits
• Time off to relax and recharge through our paid holidays, firmwide extended holidays, flexible PTO and personal sick time
• Professional development stipend
• Fertility Stipend
• Wellness/fitness benefits
• Healthy lunches provided daily
• Commuter benefits

Additional Information

• We do sponsor and take over sponsorship of employment visas for this role. If we make you an offer, we will make every reasonable effort to get you a visa.

The Data Platforms Health team builds native platform solutions that enable healthcare-specific platform capabilities. This development role in the Database Platforms department will contribute to AI-based features and workflows within the InterSystems Health Connect Cloud, InterSystems FHIR Server, InterSystems IRIS for Health and InterSystems Health Connect products.

The team needs a developer who can drive AI model and AI architecture design and development for intelligent tooling features for healthcare builders and administrators. The team also needs thought leadership to adopt evolving AI technologies so that InterSystems can be a leader in AI-driven features and workflows.

You are encouraged to apply if this role sounds interesting to you, even if you have doubts about being a competitive candidate. InterSystems prides itself on investing in its team members.

This position is in the InterSystems headquarters in Boston, MA.

Responsibilities

You will design, build, train, and deploy machine learning and agentic AI models, and consume LLMs and custom models using REST APIs. Working with product management and support specialists, you will design and implement data cleansing and feature extraction tools to improve the accuracy of predictions and data generation for a healthcare setting. Your responsibilities will include integrating the models into existing products and refining the models to meet evolving product needs.

All work must follow the team’s development workflow including use of source control, design and code reviews, and clear documentation. You are responsible for the quality of your code and must design automated tests to verify the effectiveness of the models and features.

This role will require you to respond to technical questions about expected product behavior and recommended best practices from support specialists and sales engineers. You will also collaborate with the release engineering team to ensure that your model and tools are appropriately deployed in cloud and on-prem environments.

The technology stack includes Python, AWS Bedrock, ObjectScript, and InterSystems IRIS.

As a leader, you are expected to create project plans with estimates, track execution against the plan, and proactively communicate anticipated delays in the project. With support from your manager, you will coordinate with other teams and overcome blockers and inter-team misalignments to deliver your projects. You will also provide thought leadership in the areas of Gen AI, agentic AI, and other evolving technologies, and encourage other team members to adopt these technologies for the platform.

Qualifications Required

• Bachelor’s degree in Computer Science, Engineering, or a related technical discipline.
• 8+ years of hands-on professional experience as a software developer or similar. Open to considering less experience in combination with a Graduate degree.
• Experience with data analysis, data cleansing, feature extraction, and model training.
• Experience with Python and common libraries like Pandas, NumPy, and Scikit-learn.
• Experience with model training and evaluation.
• Experience with Agent orchestration and runtime, MCP, tool registration, and multi-model routing.
• Experience with design or consumption of REST APIs.
• Strong verbal and written communication skills.

Preferred Qualifications

• Self-starter with curiosity to experiment and learn, and confidence to challenge the status quo.
• Professional experience with machine learning algorithms like neural networks and LLMs.
• Professional experience with programmatic access of LLMs and/or open-source models.
• Experience with observability of model performance and runtime costs.
• Experience with model governance and design of guardrails for model security.
• Professional experience with deep learning libraries like TensorFlow, PyTorch, or Keras.
• Professional experience with health messaging standards, especially FHIR.
• 3+ years of experience with other programming languages like Java, C#, C++, or ObjectScript.

We are an equal-opportunity employer and do not discriminate because of race, color, religion, sex, national origin, ancestry, marital status, veteran status, age, disability, sexual orientation or gender identity or expression or any other legally protected category. InterSystems is an E-Verify Employer in the United States.

About Graphcore 

At Graphcore, we’re building the future of AI compute.

We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.

As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.

To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.

We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence

Job Summary

Applicants for this role should have strong experience designing, developing, and maintaining high-quality software systems. The role focuses on testing and validating a complex machine learning software stack, with particular emphasis on software architecture, automation, and engineering best practices.

The ideal candidate is an experienced software engineer who values code quality, testability, and long-term maintainability, and enjoys building systems that other engineers rely on. This person will be comfortable working across large codebases, contributing to CI/CD infrastructure, and shaping technical direction through thoughtful design and mentoring in a technically demanding environment spanning ML frameworks, infrastructure, and AI accelerator hardware

The Team

The ML QA team is composed of highly skilled software engineers with a strong focus on automation, software quality, and data-driven validation. The team works closely with industry-standard machine learning frameworks and models, contributing to upstream open-source projects and collaborating across the wider software organization. 

Operating in a fast-paced environment, the team plays a critical role in ensuring reliability, performance, and maintainability across the ML software stack, helping to deliver robust and high-quality products to customers. 

Responsibilities and Duties

• Design, implement, and maintain robust test infrastructure and automation for a complex ML software stack.
• Architect and evolve test frameworks and tooling with a focus on scalability, maintainability, and developer experience.
• Build and maintain CI/CD pipelines targeting simulators, emulators (e.g. QEMU), and physical hardware.
• Create representative ML workloads and gain insights from their execution. (Numerical accuracy, performance analysis and benchmarking).
• Work closely with all Software development teams, supporting a culture of quality, security and maintainability.
• Review code and designs, setting a high bar for software engineering best practices.
• Mentor and support junior engineers, helping raise the overall technical capability of the team.
• Evaluate existing test strategies and infrastructure, identifying gaps and driving improvements aligned with team and organizational goals. 

Candidate Profile

Essential:

• Experience in production-quality software engineering roles.
• Strong software design and architecture skills, with experience working on large or complex systems.
• Strong proficiency in Python, including experience building and maintaining production codebases.
• Solid experience with CI/CD systems and automated testing (preferably GitHub-based workflows).
• Experience working in Linux environments.
• Familiarity with C or C++, with the ability to read, debug, and reason about low-level code when needed.
• Proven ability to mentor junior engineers and influence engineering practices within a team.
• Strong problem-solving skills and a proactive, self-directed approach to work.
• Bachelor/Master's/PhD or equivalent experience in Computer Science, Maths, Machine Learning, Data Science, or related field. 

Desirable

• Exposure to machine learning frameworks such as PyTorch, JAX, Triton, TensorFlow
• Experience with distributed workload management systems such as Kubernetes, VLLM, Keras or MLOps pipelines
• Experience working with hardware simulators or emulators (e.g. QEMU).
• Experience developing for or working with FPGA-based systems.
• Experience with people management or mentoring 

Benefits

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications

About Graphcore 

At Graphcore, we’re building the future of AI compute.

We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.

As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.

To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.

We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence

Job Summary

Applicants for this role should have strong experience designing, developing, and maintaining high-quality software systems. The role focuses on testing and validating a complex machine learning software stack, with particular emphasis on software architecture, automation, and engineering best practices.

The ideal candidate is an experienced software engineer who values code quality, testability, and long-term maintainability, and enjoys building systems that other engineers rely on. This person will be comfortable working across large codebases, contributing to CI/CD infrastructure, and shaping technical direction through thoughtful design and mentoring in a technically demanding environment spanning ML frameworks, infrastructure, and AI accelerator hardware

The Team

The ML QA team is composed of highly skilled software engineers with a strong focus on automation, software quality, and data-driven validation. The team works closely with industry-standard machine learning frameworks and models, contributing to upstream open-source projects and collaborating across the wider software organization. 

Operating in a fast-paced environment, the team plays a critical role in ensuring reliability, performance, and maintainability across the ML software stack, helping to deliver robust and high-quality products to customers. 

Responsibilities and Duties

• Design, implement, and maintain robust test infrastructure and automation for a complex ML software stack.
• Architect and evolve test frameworks and tooling with a focus on scalability, maintainability, and developer experience.
• Build and maintain CI/CD pipelines targeting simulators, emulators (e.g. QEMU), and physical hardware.
• Create representative ML workloads and gain insights from their execution. (Numerical accuracy, performance analysis and benchmarking).
• Work closely with all Software development teams, supporting a culture of quality, security and maintainability.
• Review code and designs, setting a high bar for software engineering best practices.
• Mentor and support junior engineers, helping raise the overall technical capability of the team.
• Evaluate existing test strategies and infrastructure, identifying gaps and driving improvements aligned with team and organizational goals. 

Candidate Profile

Essential:

• Experience in production-quality software engineering roles.
• Strong software design and architecture skills, with experience working on large or complex systems.
• Strong proficiency in Python, including experience building and maintaining production codebases.
• Solid experience with CI/CD systems and automated testing (preferably GitHub-based workflows).
• Experience working in Linux environments.
• Familiarity with C or C++, with the ability to read, debug, and reason about low-level code when needed.
• Proven ability to mentor junior engineers and influence engineering practices within a team.
• Strong problem-solving skills and a proactive, self-directed approach to work.
• Bachelor/Master's/PhD or equivalent experience in Computer Science, Maths, Machine Learning, Data Science, or related field. 

Desirable

• Exposure to machine learning frameworks such as PyTorch, JAX, Triton, TensorFlow
• Experience with distributed workload management systems such as Kubernetes, VLLM, Keras or MLOps pipelines
• Experience working with hardware simulators or emulators (e.g. QEMU).
• Experience developing for or working with FPGA-based systems.
• Experience with people management or mentoring 

Benefits

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications

Company Overview

At CommerceIQ, we help consumer brands accelerate their retail ecommerce market share growth and profitability through machine learning algorithms. We are building the world’s most complete and sophisticated Retail Ecommerce Management Platform, which connects and intelligently automates the management of retail ecommerce channels like Amazon, Walmart, and Instacart, across the entire ecommerce operational chain of retail media management, sales operations, supply chain, and digital self analytics.

We are in hyper growth mode, having recently raised our Series D funding at unicorn valuation (>$1B) and ended our third year of triple-digit revenue growth. Continued acceleration of our growth is fueled by landing new customers, expanding our platform through new products, managing new retail ecommerce platforms, and delivering exceptional customer service to unlock high net retention rates.

What You’ll Be Doing

As a Lead ML Engineer in the Data Science team, you will work closely with the engineering, product, and operations teams to build state-of- the-art ML based solutions for B2B SaaS products. This will entail applying advanced ML algorithms at scale for core products and developing robust end to end production pipelines which includes Human-in-the-Loop component to boost the quality. 

In this role, you will find innovative ways to apply emerging technologies to improve business processes and drive more value for customers. The ideal candidate will have a strong background in machine learning model development, natural language processing and understanding, and data analysis which they can utilize to manage and improve our company’s AI/ML initiatives. 

• Architect and Own multiple AI driven end to end pipelines that allows for deployment and scalability of machine learning models
• Build tools and capabilities that help with data ingestion to feature engineering, data management and organization
• Build tools and capabilities for scalability through distributed optimization 
• Deploy  cutting edge algorithms like LLMs etc. on GPUs at scale
• Work with stakeholders on the research and software engineering side of the company to understand how to support their teams
• Build tools and capabilities for model management and model performance monitoring
• Build operating services at scale with high availability and reliability
• Propose and implement the best engineering practices for scaling ML-powered features, with a goal to enable the fast iteration of and efficient experimentation with novel features
• Contribute and influence the ML infrastructure roadmap in collaboration with Data Science team

What we are looking for -

• Bachelor’s or Masters in Computer Science or Maths/Stats from a reputed college with 5+ years of experience in solving of experience in machine learning engineering problems 
• Experience and understanding of the entire machine learning pipeline from data ingestion to production
• Experience with machine learning operations, software engineering, and architecture
• Experience with large-scale systems including parallel computing and GPUs
• Experience architecting and building an AI pipelines that supports productionization of ML models
• Experience with MLOps systems
• Strong programming skills in a scientific computing language such as Python, SQL
• Experience using frameworks for machine learning and data science like scikit-learn, pandas, NumPy
• Experience working with ML tools such as Tensorflow, Keras, and Pytorch
• Ability to take successful, complex research ideas from experimentation to production
• Excellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams
• Good depth and breadth in machine learning (theory and practice), optimization methods, data mining, statistics and linear algebra

Why you will love to work with us -

We have multiple brands, which are among the biggest brands operating on amazon, as our customers. You will be responsible for working with their data and developing models and algorithms to drive lift in tune of hundreds of thousands of dollars.

• Opportunity to work on cutting edge technologies in text and images data like LLMs, OCR, transformer based embeddings models
• Deploy code using the most sophisticated tech stack like AWS, GCP etc.
• You will own projects end to end i.e., from exploration to final production
• You will be empowered to make decisions. It implies more responsibilities but high learning
• Immense opportunities to learn and develop ML based SaaS products for brands and get company-wide recognition
• Forget endless meetings. Get things done and start making an impact from day 1
• Work hard, have amazing fun, create history, build the future of eCommerce 
• Start-up environment with a strong culture and values to accelerate your career 

What You’ll Do
The Field Engineering team at Weights & Biases plays a vital role in ensuring customer success and adoption of our platform. As part of this team, we partner with Sales, Support, Product, and Engineering to lead technical success after the sales process. We work closely with some of the most advanced AI teams in the world, helping them build, optimize, and scale their ML and GenAI workflows across industries such as computer vision, robotics, natural language processing, and large language models (LLMs).

About the Role

We’re hiring a Post-Sales AI Solutions Engineer (AISE), Scale Customer Success to help customers successfully implement and scale AI/ML workflows and GenAI/agentic applications on Weights & Biases. You will design and deliver technical enablement and adoption programs that reach many customers at once, create reusable assets that improve self-serve success, and use product signals and feedback loops to continuously improve outcomes.

Key Responsibilities 

1. Run 1-to-many onboarding and enablement programs
   Own and deliver scalable onboarding and adoption motions (webinars, cohort sessions, group training, and office hours) that help customers get to value quickly and consistently.
2. Build reusable technical assets that drive self-serve success
   Create and maintain playbooks, reference architectures, templates, sample code/notebooks, and troubleshooting guides that standardize best practices and reduce repeated 1:1 work.
3. Operate the scaled motion using signals and feedback loops
   Use product usage signals and customer patterns to segment and trigger the right interventions, track program impact (activation, time-to-first-value, feature adoption), and feed recurring insights back to Support, Product, and Field Engineering to continuously improve the scaled journey.

Who You Are

• 3–5 years of relevant experience in a similar role
• Strong programming proficiency in Python
• Experience with deep learning frameworks (TensorFlow/Keras, PyTorch Lightning) and tools (e.g., Streamlit, LangChain)
• Familiarity with cloud platforms (AWS, GCP, Azure)
• Excellent communication and presentation skills, both written and verbal
• Organized and outcomes-driven: you can run programs, measure impact, and iterate.

Preferred

• Experience with GenAI and LLMs
• Proficiency with HuggingFace, Fastai, scikit-learn, XGBoost, LightGBM, or Ray
• Experience with hyperparameter optimization solutions
• Background in data engineering, MLOps, or LLMOps, with tools such as Docker and Kubernetes
• Familiarity with data pipeline tools

Wondering if you’re a good fit?
We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

• You love collaborating with top AI teams to solve real-world ML and GenAI challenges
• You’re curious about how to optimize AI workflows at scale
• You’re an expert in Python and ML tooling, with a passion for enabling customer success

Why Us?
We work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for takeoff, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

The base salary range for this role is $139,000 to $204,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

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 connects people to transportation to change the way we live and get around our communities. We are looking for product managers who bring exceptional creative, strategic, and analytical skills to drive forward a best in class product. Product managers at Lyft lead the integration of engineering, data science, and design to achieve the company’s vision of serving and connecting. We are looking for entrepreneurial and passionate product managers to innovate and execute across a rapidly growing, fast paced company and industry.

The Central Market Management and Applied Intelligence org is responsible for making Lyft’s most critical data driven decisions and the underlying AI/ML platforms that power hundreds of applications across the company. You will be the key product manager focused on the Agentic AI product and platform, and you will continuously evaluate opportunities and prospective use cases across the company to accelerate decision-making, and evangelize adoption of the team’s offerings. 

You will work directly with senior leaders and expert engineers and scientists guiding them on the right frameworks for the evaluation of technology bets, grounding them in the needs of the business and product teams at Lyft, and building prototypes to inspire them in feature exploration. The perfect person for this job will have deep technical expertise, thrives in environments of intellectual confrontation and loves keeping up to date with the industry. You will aim to become a trusted expert throughout the company on anything AI related. 

Responsibilities:

• Define, own and execute the roadmap of the AI platform and AI-powered marketplace products
• Define, track and periodically report on metrics and KPIs of the org, both to align the org and to showcase the achievements & the misses to leadership 
• Engage teams and users of AI platform inside the company to understand their needs, evangelize current offerings and identify gaps or opportunities in the available tools
• Write detailed product requirements, strategy and planning documents aimed at both technical and non technical audiences to drive alignment on product development, set expectations on delivery of milestones and create predictable outcomes for workstreams
• Proactively engage, research and craft proposals for areas of the company where AI platform can drive efficiency and/or increase effectiveness
• Present to non technical leadership on the progress of the team quarterly, showcasing concrete steps forward in the results driven by the tools of the team and adoption of them throughout the company
• Oversee and guide build vs buy decisions, grounding them in data and research

Experience:

• 7+ years of product management experience
• Experience driving technically complex products end to end, from inception, to launch with significant user adoption, to sunset
• Experience in managing (from product perspective) a team of software engineers and scientists, tracking the progress towards a roadmap through appropriate tools (Jira, Linear, Spreadsheets, Clickup etc)
• Experience in crafting data visualizations for the automated measurements of KPIs and metrics, starting from raw databases (SQL, Tableau, Looker, Mode, Python visualization packages etc)
• Familiarity with crafting and leading presentations to small groups at the CXO executives level and to big teams (100+ ppl) at an all hands like level in medium to large companies
• Ease in driving results and operating independently and with little supervision in flat structured organizations where approvals are not needed but results are closely monitored
• Strong understanding of agentic systems, context engineering, and multi-agent orchestration
• Strong conceptual knowledge of machine learning and AI; hands-on coding experience with standard libraries (e.g., PyTorch, Keras, Scikit-learn, XGBoost) is a plus
• Experience in handling third parties as vendors or customers and knowledge of Saas contract practices and software sales processes
• Excellent skills in documenting and articulating complex technical systems.

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

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 3 days per week 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 San Francisco area is $176,000 - $220,000, 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.

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.

As a Data Scientist on the Mapping team, you will collaborate with our world class team of engineers, product managers, and designers to grow and improve the quality of recommended routes and accuracy of our travel time estimations. We're looking for a passionate, driven Data Scientist who is excited to dive into our spatial data and build a best-in-class mapping product that provides safe, efficient, and seamless navigation for our rideshare drivers.

Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our mapping products and make business decisions that put our customers first. This will involve identifying and scoping opportunities, shaping priorities, recommending technical solutions, designing experiments, and measuring the impact of new features. You will help us solve some of the most impactful problems in mapping, including:

• How do we improve the quality of our map data in order to improve our recommendations?
• How do we benchmark and measure the success of our services?
• How do we validate features of the real world that affect our routing algorithms?
• Are we meeting our travel estimation promises to our customers?

Responsibilities

• Leverage data and analytic frameworks to identify opportunities for growth and efficiency
• Partner with product managers, engineers, and operators to translate analytical insights into decisions and action, and implement products to drive business goals
• Define and implement decision frameworks, measurement strategies, and scientific methodologies that bring consistency and rigor to business decisions and forecasts, balancing opportunity and uncertainty
• Deliver integrated, high-quality analytical outputs spanning multiple projects while navigating ambiguity, cross-team dependencies, and open-ended scope
• Design and analyze online experiments; communicate results and act on launch decisions
• Establish metrics that measure the health of our products, as well as rider and driver experience
• Identify and drive impact and alignment, shaping product and business strategy through data-centric presentations 
• Contribute to the Science community (hiring, onboarding, documentation, knowledge-sharing, tooling improvements), helping make Decision Science at Lyft more effective and scalable

Experiences

• Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience
• 3+ years experience in a data science role or analytics role
• Demonstrated ability to own multi-project analytical scopes with ambiguous problem definitions and cross-functional integration
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Proficiency in SQL - able to write structured and efficient queries on large data sets
• Experience in programming, especially with data science and visualization libraries in Python or R, and machine learning libraries such as PyTorch, TensorFlow, Keras
• Experience in online experimentation and statistical analysis, and communicating results and recommendations to senior stakeholders
• Strong communication, critical thinking, and prioritization skills, including the ability to challenge assumptions, propose alternatives, and balance short-term vs. long-term tradeoffs
• Experience in applying machine learning techniques is a plus (e.g. reinforcement learning) to solve customer problems (e.g. personalization, segmentation)
• Expertise in metric design, causal analysis, behavioral analytics, decision frameworks and measurement strategy is a plus
• Experience working with ETL pipelines a plus

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 $108,000 - $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.

As a Senior Machine Learning Engineer in Computer Vision, you will design and deliver advanced vision systems that power mission-critical applications for global and Fortune 500 companies. You’ll work across deep learning, large-scale data pipelines, and high-performance infrastructure, owning models end-to-end from experimentation to production deployment.

This role is designed for engineers who think systems-level, understand the real-world constraints of ML at scale, and can turn ambiguous visual problems into high-impact, production-ready solutions. You’ll shape architectures, guide model strategy, and bring modern vision capabilities into enterprise environments where reliability, speed, and accuracy matter.

Functional Responsibilities:

• Develop and fine-tune models for tasks like image classification, object detection, segmentation, and generative modeling using TensorFlow, PyTorch, or Keras.
• Implement techniques such as resizing, normalization, data augmentation, and feature extraction to improve model performance.
• Optimize and deploy computer vision models on cloud platforms (AWS, GCP, Azure), edge devices, and specialized hardware (GPUs, TPUs).
• Use CI/CD, model versioning, and monitoring tools to ensure reliable and scalable deployment of vision models.
• Improve model speed and performance using quantization, pruning, and hardware acceleration techniques.

Qualifications:

• +5 years of hands-on experience developing and deploying machine learning models in production environments. 
• Proven experience writing production-level code, with strong proficiency in Python.
• Strong Python programming skills with proficiency in deep learning frameworks (TensorFlow, PyTorch, or Keras).
• Expertise in designing, training, and fine-tuning models for: Image classification (ResNet, EfficientNet), Object detection (Faster R-CNN, YOLO, SSD) or Image segmentation (U-Net, Mask R-CNN).
• Strong understanding of image preprocessing techniques (resizing, normalization, data augmentation).
• Experience with computer vision libraries such as OpenCV and torchvision.
• Experience with transfer learning and adapting pre-trained models.
• Ability to deploy models on cloud platforms (AWS, GCP, Azure) and specialized hardware (GPUs, TPUs).
• Familiarity with MLOps tools for automating ML pipelines.

About the team & opportunity 

What’s so great about working on Calendly’s Data Science & Machine Learning team? 

We make things possible for our customers through innovation in data, analytics and AI.

Why do we need you? Well, we are looking for a Machine Learning Engineer who will deliver business value by executing the full machine learning lifecycle hands-on, from problem discovery through model deployment and monitoring. You will report to the head of Data Science & Machine Learning and will be responsible for building and operating ML-powered features that create magical experiences for our customers.

Our team:

• Drives business insights, strategic decision making, executive level and cross organizational business growth, and magical customer experiences for our end customers through impactful innovation.
• Works closely with product, design, marketing, customer success, and engineering teams to implement ML models that improve the customer journey in service to growth and efficiency (for example, understanding the relationships among customers’ behavior and business performance).
• Has a strong product focus and passion for using machine learning to solve real world problems, and understands that being an effective MLE is about collaborating with people as much as it is about writing code.

You will join a high performing AI team and be an integral part of building new, machine learning based experiences for internal and external customers alike.

What you’ll do

On a typical day, you’ll own features end to end within our ML ecosystem, with growing independence and impact.

• Own ML powered features from design through deployment, partnering with product, design, and engineering to scope work and define success metrics.
• Understand and share domain knowledge, answering domain specific questions for your product area and documenting what you learn for the team.
• Prioritize your work independently, balancing feature development, quality, and maintenance, and communicating tradeoffs clearly.
• Proactively seek and offer support to teammates pairing, reviewing, and collaborating to move projects forward.
• Understand and troubleshoot our deployment pipelines, including build, test, and release steps for ML services and data pipelines.
• Use our monitoring and observability tools to effectively triage alerts and incidents, collaborating with partners to restore service and prevent recurrence, and participate in the team’s on-call rotation and incident response. 
• Serve as a subject matter expert for the features and services you own, including their data contracts, SLAs, and dependencies.
• Be a frequent user of AI Tools and champion of adoption to the rest of the company.  

What do we need from you?

• 4+ years of industry experience in applied Machine Learning or closely related fields (or equivalent combination of education and experience) with a demonstrated track record of shipping and operating ML models in production.
• Deep and demonstrated ability to traverse the full spectrum of ML life cycle: exploratory data analysis, feature engineering, data visualization, feature and algorithm selection, model experimentation, model training and validation, model serving, monitoring and retraining
• Experience developing and implementing statistical and ML models to uncover patterns, trends, and predictions in areas such as revenue forecasting, churn analysis, personalization and recommendation, anomaly detection, or natural language processing.
• Hands-on experience implementing ML models using a managed service (for example, Vertex AI or SageMaker) for high-traffic, low-latency, large-data applications that produced tangible impact for end users.
• Understanding of foundation models and the open-source ecosystem, including model fine-tuning and prompt engineering for real product use cases.
• Strong programming (Python / Scala / Java / SQL etc) and data engineering skills
• Proficiency in ML frameworks such as: Keras, Tensorflow and PyTorch and ETL and ML workflow frameworks like Apache Spark, Beam, Airflow and VertexAI
• Experience working with time series data and related machine learning problems. Working knowledge of semantic search and embeddings 
• Recognize when to seek assistance and willing to learn whatever is needed to get the job done; curiosity and growth mindset are essential. 
• You have strong verbal and written communication skills. Ability to communicate complex technical concepts to both technical and business stakeholders. You are comfortable working remotely and with enabling tools like Slack, Confluence, etc.
• Authorized to work lawfully in the United States of America as Calendly does not engage in immigration sponsorship at this time 
  
  

What’s in it for you? 

Ready to make a serious impact? Millions of people already rely on Calendly’s products, and we’re still in the midst of our growth curve — it’s a fantastic time to join us. Everything you’ll work on here will accelerate your career to the next level. If you want to learn, grow, and do the best work of your life alongside the best people you’ve ever worked with, then we hope you’ll consider allowing Calendly to be a part of your professional journey. 

Our Hiring Process:

We aim to provide an inclusive and equitable candidate experience to everyone who expresses interest in working at Calendly. To learn more about our hiring process, please visit our careers page at www.careers.calendly.com.

Once selected for an opportunity, the recruiter assigned to the role will keep you informed every step of the way. Have questions? Let your recruiter know! Want to share your experience? We are passionately committed to improving and building on our process, and we consider feedback a gift. 

If you are an individual with a disability and would like to request a reasonable accommodation as part of the application or recruiting process, please contact us at recruiting@calendly.com . 

Calendly is registered as an employer in many, but not all, states. If you are located in Alaska, Alabama, Delaware, Hawaii, Idaho, Montana, North Dakota, South Dakota, Nebraska, Iowa, West Virginia, and Rhode Island, you will not be eligible for employment. Note that all individual roles will specify location eligibility.

All candidates can find our Candidate Privacy Statement here

Candidates residing in California may visit our Notice at Collection for California Candidates here: Notice at Collection

OPEN POSITION ANNOUNCEMENT!

Data Engineer

Open until filled.

Posted 4/29/2026 San Diego County – hybrid work schedule set by SDCP

About the role:  The San Diego Community Power (SDCP) is seeking a seasoned Data Engineer to join our growing team of analytics experts who will be responsible for designing, maintaining, expanding, and optimizing our data infrastructure for data collection, management, transformation, and access. A key priority of this role will be to assist in SDCP’s development of centralizing its data eco-system to allow for creation of pipelines that convert raw data into usable formats for data analysts and other data consumers to utilize. The Data Engineer will handle the core data aspects of software engineering and data science and utilize software engineering principles to develop algorithms that automate the data flow process. They will collaborate with data and system analysts to build machine learning and analytics infrastructure from testing to deployment. 

WHO IS SAN DIEGO COMMUNITY POWER?

San Diego Community Power is a community-driven, not-for-profit public agency providing cleaner energy to the San Diego region. Formed in 2019, Community Power is the second largest Community Choice Aggregator (CCA) in California, serving nearly 1 million customer accounts across its member agencies: the Cities of San Diego, Chula Vista, Encinitas, Imperial Beach, La Mesa and National City, as well as the unincorporated areas of San Diego County.  

OUR HISTORY

San Diego Community Power was formed in 2019 as a public, not-for-profit community choice aggregator (CCA) in the San Diego region. We began electric service in 2021 and serve five member agencies: San Diego, Chula Vista, Encinitas, La Mesa and Imperial Beach, County of San Diego, and National City. SDCP was formed to bring local control and customer choice to San Diego while also providing clean and renewable energy at competitive rates. By the end of 2023, SDCP will provide electricity for nearly half the electric load in San Diego Gas and Electric’s service territory and will be the second largest CCA in California. For more information, please visit SDCommunityPower.org.

COMMITMENT TO DIVERSITY

At SDCP, we value diversity and are committed to creating an inclusive environment for all employees. We represent a diverse customer base and hope to hire employees that reflect our communities. We provide equal employment opportunities to all applicants for employment and prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. 

ESSENTIAL DUTIES AND PRIMARY RESPONSIBILITES

• Building and maintaining a centralized cloud-based data infrastructure for optimal extraction, transformation, and loading of data from a wide variety of sources. 
• Assemble large, complex data sets that meet functional/non-functional business requirements. 
• Developing data tools and APIs for data analysis. 
• Deploying and monitoring machine learning algorithms and statistical methods in production environments to solve organizational needs. 
• Ensuring data accessibility and security and implementing company data policies regarding data privacy and confidentiality. 
• Improving data systems reliability, speed, and performance. 
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer trends, operational efficiency, and other key business performance metrics. 
• Collaborating with other internal teams, data analysts, and other stakeholders to understand and optimize how data can be leveraged to meet business needs. 
• Assist in drafting data and analytics’ solicitations and in the selection of consultants. 
• Assist with drafting staff reports and presentations for Board and Committee meetings. 
• Performs other related duties and responsibilities as required. 

MINIMUM KNOWLEDGE, SKILLS, AND ABILITES

• Advance working knowledge of SQL, experience working with relational databases, query authoring (SQL) and working familiarity with various databases. 
• Demonstrated experience in developing API and integrations to support analytics in cloud environment. 
• Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets. 

• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. 
• Strong analytic skills related to working with unstructured datasets. 
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management. 
• A successful history of manipulating, processing, and extracting value from large, disconnected datasets. 
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores. 
• Good understanding of data architecture, data design, data warehousing and data modeling concepts. 
• Strong project management and organizational skills. 
• Experience supporting and working with cross-functional teams in a dynamic environment. 

PREFERRED KNOWLEDGE, SKILLS, AND ABILITES

• Experience in the energy sector and/or supporting the implementation of programs funded by California state agencies (e.g., California Public Utilities Commission, California Energy Commission, California Air Resources Board).
• Ability to strongly represent the organization in various professional engagement settings from local to national convenings (conferences, workshops, executive meetings, etc.).

PREFERRED QUALIFICATIONS, EDUCATION AND EXPERIENCE

Minimum of two (2) to three (3) years of professional experience in a Data Engineer role, preferably in the energy industry with a graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. The candidate should also have experience using the following software/tools:

• Experience with big data tools: Hadoop, Spark, PowerBI, Kafka, etc.
• Experience with AWS, Azure and Google Cloud services.
• Experience with relational SQL and NoSQL databases.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• Experience with open-source technologies: Python, Pytorch, Flask, Tensorflow or Keras
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Java, C++ etc.
• Experience with batch, micro-batching and real-time data ingestion methodologies.
• Experience with GitHub or similar code repositories

WORK ENVIROMENT & CONDITIONS

Prolonged periods sitting at a desk and working on a computer. The position requires occasional carrying, lifting and/or moving objects up to 25 pounds. Occasional local travel required and reliable transportation to be able to attend SDCP events, meetings, and workshops as needed is expected. At SDCP we work in the communities we serve and in the office. SDCP works to ensure a safe and healthy workplace for employees and in our communities. SDCP requires employees to be fully vaccinated for COVID-19. SDCP is an agency required to adopt and promulgate a Conflict-of-Interest Code (“COI”). The COI code requires employees in designated positions, including those identified under the interim disclosure process to file a Statement of Economic Interests (Form 700) on an annual basis. A Successful candidate accepting this position may be required to file Conflict of Interest forms subject to the regulations of the Fair Political Practices Commission.

COMPENSATION: 

Salary Range: The position salary range is: $84,900 - $110,400; with exact compensation to be determined by SDCP, depending upon experience. 

Benefits: Standard benefits package including but not limited to:

Insurance: SDCP offers group health benefits, including medical, vision, and dental insurance, for eligible FT employees. Also provided is a $100,000 Life & AD&D policy, STD and LTD coverage that is 100% paid by SDCP.

Retirement: SDCP offers a 457(b) plan for employee contributions and contributes 10% of eligible compensation to the employee’s Money Purchase Plan.

Paid Time Off: 11 holidays per year + paid winter holiday (between 12/24-12/31), 160 hours of accrued paid time off per year (increases with time in service), and 96 hours per year of accrued paid sick leave.

This job description may not be inclusive of all assigned duties, responsibilities, or aspects of the job described, and may be amended at the discretion of SDCP as needed. 

The Role

The Risk Data Science team is looking for a Data Scientist/Senior Data Scientist to develop advanced machine learning and statistical models, guide measurement, strategy, and data-driven decision making to support various credit risk and operational areas at SoFi. The Data Scientist will work closely with Credit, Risk, Product, Engineering, and Operations teams to design solutions for underwriting, portfolio management, loss mitigation, and loss forecasting etc. These tasks involve researching and applying state of the art modeling methodologies to solve complex business problems. This role is very rewarding as your work will have a direct and immediate impact on the business’ profitability.

What You’ll Do

• Develop, implement, and continuously improve machine learning and statistical models that support various credit, risk, and operational procedures including but not limited to underwriting, portfolio management, loss mitigation, and loss forecasting, etc.
• Present model performance and insights to Credit, Risk, and Business Unit leaders.
• Proactively identify opportunities to apply advanced modeling approaches to solve complex business problems.
• Explore and leverage in-house and external data sources to enhance model predictive power.
• Collaborate with the Model Risk Management team to demonstrate models are developed with high level rigor that satisfy Model Risk Management and Governance requirements. 
• Perform ongoing monitoring of the models through the construction of dashboards and KPI tracking
• Collaborate with the Product and Engineering teams to improve the model development, deployment, monitoring, and model re-calibration/re-build process..
• Explore and apply in-house and open-source machine learning and statistical tools and algorithms to develop and improve models.

What You’ll Need

• Master’s degree in Statistics, Econometrics, Mathematics, Operations Research, Physics, Computer Science, Engineering, or quantitative field required. PhD degree preferred.
• 2+ years of relevant work experience in building and implementing machine learning and statistical models.
• Excellent logic reasoning and communication abilities when interpreting business requirements and translating them into effective data solutions.
• Strong skills in writing efficient SQL queries and Python code to create complex attributes, especially with large datasets.
• Strong sensitivity to details in data and proactively investigate them to uncover unknown patterns.
• Strong knowledge of databases and related languages/tools such as SQL, NoSQL, Hive, etc. 
• Demonstrated sophisticated experience in building efficient and reliable pipelines that interact with large datasets stored in SageMaker and Snowflake, automating recurring processes such as data extraction and processing, feature selection, model training, model monitoring, and generating documentation templates to support reproducibility and cross-functional collaboration.
• Excellent knowledge of machine learning and statistical modeling methods for supervised and unsupervised learning. These methods include (but are not limited to) regression, classification, clustering, outlier detection, novelty detection, decision trees, nearest neighbors, support vector machines, ensemble methods and boosting, neural networks, deep learning and its various applications. Continuously following the advancement of machine learning and artificial intelligence to update your knowledge and skills in order to solve business problems with the most efficient methodologies
• Strong programming skills in Python and machine learning libraries (e.g., sklearn, lightgbm, xgboost, pytorch, tensorflow, keras, etc.)

Nice To Have

• Experience in a lending organization.
• Experience with model documentation and delivering effective verbal and written communication.
• Experience in working closely with Product, Engineering, and Model Risk Management teams.
• Experience with AWS or GCP.

THE POSITION
Our roster has an opening with your name on it

At FanDuel, data is the heartbeat of our organization.  As a Machine Learning Engineer at FanDuel, you will help us unlock the full potential of our vast amounts of real-time and relational data. You will be asked to provide our business with insight and our customers with world-class personalized experiences.  Every click our users make, every bet, every touchdown, every fumble, and every play is fair game for us to turn into a stream of knowledge. Your expertise will be used here to make better and faster decisions – outpacing our competition.

Collaboration is at the core of your role. You’ll be the linchpin between engineering teams working downstream to build out our online application and upstream to land necessary data for feature engineering. You’ll also be working with Data Scientists and Analysts to productionize, analyze, and validate AI powered insights. You will be asked to help organize, model, and present our data as a coherent product and offer it to our stakeholders, providing a common information framework that allows FanDuel to intelligently react to what is happening on the field and in the marketplace.   

We are looking for Senior Machine Learning Engineer who may be looking to make the move to a big data environment.  If this describes you, read on – we want to hear from you!

THE GAME PLAN
Everyone on our team has a part to play

• Designing and implementing intelligent search system incorporating typeahead search, vector search and ML personalization model signals to optimize relevance and user experience
• Contributing to the design and development of scalable serving systems for ML and GenAI/LLM models
• Developing platform features and capabilities (e.g. CLI, SDK, Infra Automation, Platform Applications) for streamlining ML Model and GenAI/LLM Application development and deployment lifecycle
• Business intelligence tools (e.g., Tableau, Knime, Looker)
• Data security and privacy (e.g. GDPR, CPP)
• Data governance and data testing frameworks
• Continuous integration and delivery of production data products
• An inclusive culture that expects excellence and priorities your growth as an engineer and your well-being as a person
• Advance your career within well-defined, skill-based tracks, either as an individual contributor or as a manager – both providing equal opportunities for compensation and advancement
• Collaborating with peers and sharing best practices in system reliability, automation, and data quality

ML engineering is a rapidly changing field – most of all, we’re looking for someone who enjoys experimenting, keeping their finger on the pulse of current data engineering tools, and always thinking about how to do something better.

THE STATS
What we're looking for in our next teammate

• 5-7+ years of relevant experience developing code in one or more core programming languages (Python, Java, etc.)
• 1+ Years of Experience implementing vector search, semantic search, or embedding-based retrieval systems for production ML or AI applications
• 1+ Years of Experience working with typeahead / autocomplete systems and integrating ML signals into query understanding or ranking workflows
• 1+ Years of Experience combining outputs from multiple retrieval systems (e.g., vector search + typeahead + personalization models) to improve relevance
• 1+ Years of experience in deploying ML and GenAI/LLM models under the constraints of scalability, correctness, and maintainability.
• Hands on experience with ML frameworks and libraries (Scikit-learn, Pytorch, Tensorflow, LightGBM, Keras, MLFlow etc.) and familiarity with LLM-specific frameworks (e.g., LangChain, Hugging Face Transformers, etc).
• Hands on experience with one or more ML and GenAI/LLM cloud services (Amazon SageMaker, Amazon Bedrock, Databricks Mosaic AI, Seldon, Arize, etc)
• 4+ Years of experience designing and building various software architecture, with some emphasis on scalable architectures supporting both traditional ML and advanced LLM workflows.
• Deep understanding and knowledge of data structures, distributed computing, and software engineering principles
• 3+ Years of experience demonstrating technical leadership working with teams, owning projects, defining, and setting technical direction for projects.
• Experience with one or more relevant tools (Flink, Spark, Sqoop, Flume, Kafka, Amazon Kinesis, Terraform, Airflow)
• Ability to share findings in easy to consume formats, whether that is through dashboards or data modeling.
• Conduct regular design process reviews and ensure development standards within the team.
• Working with leadership to drive adoption of ML and GenAI/LLM solutions to product engineering teams.
• Experience working in a cloud environment such as AWS, GCP, Azure.
• Experience with Databricks is a plus, their unity catalog, another plus.
• Designing and building data pipelines for production level ML and GenAI/LLM infrastructure.
• Experience with vector databases to efficiently manage and retrieve embeddings for LLM applications, enabling high-performance similarity search and retrieval-augmented generation (RAG) workflows is a plus
• Motivate junior engineers on best practices and latest industry design patterns.

ABOUT FANDUEL

FanDuel Group is the premier mobile gaming company in the United States and Canada. FanDuel Group consists of a portfolio of leading brands across mobile wagering including: America’s #1 Sportsbook, FanDuel Sportsbook; its leading iGaming platform, FanDuel Casino; the industry’s unquestioned leader in horse racing and advance-deposit wagering, FanDuel Racing; and its daily fantasy sports product.  

In addition, FanDuel Group operates FanDuel TV, its broadly distributed linear cable television network and FanDuel TV+, its leading direct-to-consumer OTT platform. FanDuel Group has a presence across all 50 states, Canada, and Puerto Rico.

The company is based in New York with US offices in Los Angeles, Atlanta, and Jersey City, as well as global offices in Canada and Scotland. The company’s affiliates have offices worldwide, including in Ireland, Portugal, Romania, and Australia.

FanDuel Group is a subsidiary of Flutter Entertainment, the world's largest sports betting and gaming operator with a portfolio of globally recognized brands and traded on the New York Stock Exchange (NYSE: FLUT).

PLAYER BENEFITS
We treat our team right

We offer amazing benefits above and beyond the basics. We have an array of health plans to choose from (some as low as $0 per paycheck) that include programs for fertility and family planning, mental health support, and fitness benefits. We offer generous paid time off (PTO & sick leave), annual bonus and long-term incentive opportunities (based on performance), 401k with up to a 5% match, commuter benefits , pet insurance, and more - check out all our benefits here: FanDuel Total Rewards. *Benefits differ across location, role, and level.

FanDuel is an equal opportunities employer and we believe, as one of our principles states, “We are One Team!”. As such, we are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or any other characteristic protected by state, local or federal law. We believe FanDuel is strongest and best able to compete if all employees feel valued, respected, and included.

The applicable salary range for this position is $138,000 - $173,000 USD, which is dependent on a variety of factors including relevant experience, location, business needs and market demand. This role may offer the following benefits: medical, vision, and dental insurance; life insurance; disability insurance; a 401(k) matching program; among other employee benefits. This role may also be eligible for short-term or long-term incentive compensation, including, but not limited to, cash bonuses and stock program participation. This role includes paid personal time off and 14 paid company holidays. FanDuel offers paid sick time in accordance with all applicable state and federal laws.

FanDuel is committed to providing reasonable accommodations for qualified individuals with disabilities. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please email Benefits@fanduel.com.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

THE POSITION
Our roster has an opening with your name on it

At FanDuel, data is the heartbeat of our organization.  As a Machine Learning Engineer at FanDuel, you will help us unlock the full potential of our vast amounts of real-time and relational data. You will be asked to provide our business with insight and our customers with world-class personalized experiences.  Every click our users make, every bet, every touchdown, every fumble, and every play is fair game for us to turn into a stream of knowledge. Your expertise will be used here to make better and faster decisions – outpacing our competition.

Collaboration is at the core of your role. You’ll be the linchpin between engineering teams working downstream to build out our online application and upstream to land necessary data for feature engineering. You’ll also be working with Data Scientists and Analysts to productionize, analyze, and validate AI powered insights. You will be asked to help organize, model, and present our data as a coherent product and offer it to our stakeholders, providing a common information framework that allows FanDuel to intelligently react to what is happening on the field and in the marketplace.   

We are looking for Senior Machine Learning Engineer who may be looking to make the move to a big data environment.  If this describes you, read on – we want to hear from you!

THE GAME PLAN
Everyone on our team has a part to play

• Designing and implementing intelligent search system incorporating typeahead search, vector search and ML personalization model signals to optimize relevance and user experience
• Contributing to the design and development of scalable serving systems for ML and GenAI/LLM models
• Developing platform features and capabilities (e.g. CLI, SDK, Infra Automation, Platform Applications) for streamlining ML Model and GenAI/LLM Application development and deployment lifecycle
• Business intelligence tools (e.g., Tableau, Knime, Looker)
• Data security and privacy (e.g. GDPR, CPP)
• Data governance and data testing frameworks
• Continuous integration and delivery of production data products
• An inclusive culture that expects excellence and priorities your growth as an engineer and your well-being as a person
• Advance your career within well-defined, skill-based tracks, either as an individual contributor or as a manager – both providing equal opportunities for compensation and advancement
• Collaborating with peers and sharing best practices in system reliability, automation, and data quality

ML engineering is a rapidly changing field – most of all, we’re looking for someone who enjoys experimenting, keeping their finger on the pulse of current data engineering tools, and always thinking about how to do something better.

THE STATS
What we're looking for in our next teammate

• 5-7+ years of relevant experience developing code in one or more core programming languages (Python, Java, etc.)
• 1+ Years of Experience implementing vector search, semantic search, or embedding-based retrieval systems for production ML or AI applications
• 1+ Years of Experience working with typeahead / autocomplete systems and integrating ML signals into query understanding or ranking workflows
• 1+ Years of Experience combining outputs from multiple retrieval systems (e.g., vector search + typeahead + personalization models) to improve relevance
• 1+ Years of experience in deploying ML and GenAI/LLM models under the constraints of scalability, correctness, and maintainability.
• Hands on experience with ML frameworks and libraries (Scikit-learn, Pytorch, Tensorflow, LightGBM, Keras, MLFlow etc.) and familiarity with LLM-specific frameworks (e.g., LangChain, Hugging Face Transformers, etc).
• Hands on experience with one or more ML and GenAI/LLM cloud services (Amazon SageMaker, Amazon Bedrock, Databricks Mosaic AI, Seldon, Arize, etc)
• 4+ Years of experience designing and building various software architecture, with some emphasis on scalable architectures supporting both traditional ML and advanced LLM workflows.
• Deep understanding and knowledge of data structures, distributed computing, and software engineering principles
• 3+ Years of experience demonstrating technical leadership working with teams, owning projects, defining, and setting technical direction for projects.
• Experience with one or more relevant tools (Flink, Spark, Sqoop, Flume, Kafka, Amazon Kinesis, Terraform, Airflow)
• Ability to share findings in easy to consume formats, whether that is through dashboards or data modeling.
• Conduct regular design process reviews and ensure development standards within the team.
• Working with leadership to drive adoption of ML and GenAI/LLM solutions to product engineering teams.
• Experience working in a cloud environment such as AWS, GCP, Azure.
• Experience with Databricks is a plus, their unity catalog, another plus.
• Designing and building data pipelines for production level ML and GenAI/LLM infrastructure.
• Experience with vector databases to efficiently manage and retrieve embeddings for LLM applications, enabling high-performance similarity search and retrieval-augmented generation (RAG) workflows is a plus
• Motivate junior engineers on best practices and latest industry design patterns.

ABOUT FANDUEL

FanDuel Group is the premier mobile gaming company in the United States and Canada. FanDuel Group consists of a portfolio of leading brands across mobile wagering including: America’s #1 Sportsbook, FanDuel Sportsbook; its leading iGaming platform, FanDuel Casino; the industry’s unquestioned leader in horse racing and advance-deposit wagering, FanDuel Racing; and its daily fantasy sports product.  

In addition, FanDuel Group operates FanDuel TV, its broadly distributed linear cable television network and FanDuel TV+, its leading direct-to-consumer OTT platform. FanDuel Group has a presence across all 50 states, Canada, and Puerto Rico.

The company is based in New York with US offices in Los Angeles, Atlanta, and Jersey City, as well as global offices in Canada and Scotland. The company’s affiliates have offices worldwide, including in Ireland, Portugal, Romania, and Australia.

FanDuel Group is a subsidiary of Flutter Entertainment, the world's largest sports betting and gaming operator with a portfolio of globally recognized brands and traded on the New York Stock Exchange (NYSE: FLUT).

PLAYER BENEFITS
We treat our team right

We offer amazing benefits above and beyond the basics. We have an array of health plans to choose from (some as low as $0 per paycheck) that include programs for fertility and family planning, mental health support, and fitness benefits. We offer generous paid time off (PTO & sick leave), annual bonus and long-term incentive opportunities (based on performance), 401k with up to a 5% match, commuter benefits , pet insurance, and more - check out all our benefits here: FanDuel Total Rewards. *Benefits differ across location, role, and level.

FanDuel is an equal opportunities employer and we believe, as one of our principles states, “We are One Team!”. As such, we are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or any other characteristic protected by state, local or federal law. We believe FanDuel is strongest and best able to compete if all employees feel valued, respected, and included.

The applicable salary range for this position is $138,000 - $173,000 USD, which is dependent on a variety of factors including relevant experience, location, business needs and market demand. This role may offer the following benefits: medical, vision, and dental insurance; life insurance; disability insurance; a 401(k) matching program; among other employee benefits. This role may also be eligible for short-term or long-term incentive compensation, including, but not limited to, cash bonuses and stock program participation. This role includes paid personal time off and 14 paid company holidays. FanDuel offers paid sick time in accordance with all applicable state and federal laws.

FanDuel is committed to providing reasonable accommodations for qualified individuals with disabilities. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please email Benefits@fanduel.com.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

WHAT YOU'LL DO

As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:

• Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration
• Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components
• Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms
• Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise
• Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success

WHO YOU ARE

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
• Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
• Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
• Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $98,000-$164,000/year, with an expected On Target Earnings (OTE) between $109,000-$183,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

#LI-Hybrid

WHAT YOU'LL DO

As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:

• Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration
• Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components
• Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms
• Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise
• Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success

WHO YOU ARE

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
• Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
• Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
• Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $98,000-$164,000/year, with an expected On Target Earnings (OTE) between $109,000-$183,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

#LI-Hybrid

WHAT YOU'LL DO

As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:

• Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration
• Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components
• Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms
• Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise
• Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success

WHO YOU ARE

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
• Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
• Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
• Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $98,000-$164,000/year, with an expected On Target Earnings (OTE) between $109,000-$183,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

#LI-Hybrid

WHAT YOU'LL DO

As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:

• Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration
• Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components
• Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms
• Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise
• Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success

WHO YOU ARE

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
• Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
• Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
• Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $98,000-$164,000/year, with an expected On Target Earnings (OTE) between $109,000-$183,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

#LI-Hybrid

Bloomreach is seeking a seasoned Senior Machine Learning Engineer to own the design and implementation of cutting-edge AI and GenAI driven algorithmic components for contextual personalization, predictions and behavioral insights that are used to personalize digital experiences for our customers. We are currently allowing flexibility for our employees to work from anywhere for the respective region (Central & Eastern Europe) or we are happy to meet you in our offices in Bratislava (Slovakia) or Brno, Prague (Czechia) on a full-time basis. The salary starts at €4,800 gross per month, along with restricted stock units and other benefits. 

Your Responsibilities:

• Design, develop, and enhance ML/AI models which Predictions, Contextual Personalization and our new agentic workflows
• Process historical data, product catalog and user behaviours to extract hidden relations and features.
• Conduct research to explore ongoing cutting-edge ML techniques and conduct a quick POC.
• Work closely with ML Engineers to integrate and scale ML components to a production-level that can handle terabytes of data.
• Continuously learn and stay up to date with the current state-of-the-art techniques by reading research papers and attending AI/ML conferences.

Qualifications:

• BS/MS degree in Computer Science or a related discipline with a strong mathematical foundation and excellent programming skills (primarily Python)
• At least 3 years of experience building ML-driven fast and scalable ML/analytical algorithms in a corporate/startup environment.
• Strong awareness and understanding of recent trends in Generative AI and LLMs. Experience in working with GenAI stack will be treated as strong credentials.
• Strong understanding of various machine learning and natural language processing technologies, such as classification, information retrieval, clustering, knowledge graph, semi-supervised learning and ranking.
• Excellent exploratory data analysis skills with the ability to slice and dice data at scale using SQL in BigQuery.
• Good problem solving and analytical skills. Ability to learn and adapt to newer ML technologies.
• Exposure to deep learning stack (PyTorch/Keras/TensorFlow) and techniques (Representation/Transfer Learning, RNN/LSTM, Transformers).
• Experience working with Big Data in a cloud based production environment (AWS/GCP/Azure).
• Effective communication skills in English, both verbally and in written form.

#LI-KP1

Bloomreach is seeking a seasoned Senior Machine Learning Engineer to own the design and implementation of cutting-edge AI and GenAI driven algorithmic components for contextual personalization, predictions and behavioral insights that are used to personalize digital experiences for our customers. We are currently allowing flexibility for our employees to work from anywhere for the respective region (Central & Eastern Europe) or we are happy to meet you in our offices in Bratislava (Slovakia) or Brno, Prague (Czechia) on a full-time basis.

Your Responsibilities:

• Design, develop, and enhance ML/AI models which Predictions, Contextual Personalization and our new agentic workflows
• Process historical data, product catalog and user behaviours to extract hidden relations and features.
• Conduct research to explore ongoing cutting-edge ML techniques and conduct a quick POC.
• Work closely with ML Engineers to integrate and scale ML components to a production-level that can handle terabytes of data.
• Continuously learn and stay up to date with the current state-of-the-art techniques by reading research papers and attending AI/ML conferences.

Qualifications:

• BS/MS degree in Computer Science or a related discipline with a strong mathematical foundation and excellent programming skills (primarily Python)
• At least 3 years of experience building ML-driven fast and scalable ML/analytical algorithms in a corporate/startup environment.
• Strong awareness and understanding of recent trends in Generative AI and LLMs. Experience in working with GenAI stack will be treated as strong credentials.
• Strong understanding of various machine learning and natural language processing technologies, such as classification, information retrieval, clustering, knowledge graph, semi-supervised learning and ranking.
• Excellent exploratory data analysis skills with the ability to slice and dice data at scale using SQL in BigQuery.
• Good problem solving and analytical skills. Ability to learn and adapt to newer ML technologies.
• Exposure to deep learning stack (PyTorch/Keras/TensorFlow) and techniques (Representation/Transfer Learning, RNN/LSTM, Transformers).
• Experience working with Big Data in a cloud based production environment (AWS/GCP/Azure).
• Effective communication skills in English, both verbally and in written form.

#LI-KP1

Bloomreach is seeking a seasoned Staff Machine Learning Engineer to own the design and implementation of cutting-edge AI and GenAI driven algorithmic components for search, recommendation and behavioral insights that are used to personalize digital experiences for our customers. Our centralized data science team spanned across multiple geographies, is responsible for the data science modules that power all the products of the company, including Search Relevance, Recommendation, User Personalization, User Segmentations, Content Intelligence and Conversational Commerce. We invent and apply machine learning, data mining, and information retrieval algorithms to understand, identify, and improve web content discovery. We have built industry leading algorithms in search and recommendations for the commerce space that serve the most relevant experiences using Artificial Intelligence with the goal-building AI driven experiences beyond commerce.

Your Responsibilities:

• Design, develop, and enhance ML/AI models which mainly power Search and Recommendation.
• Process historical data, search queries, product catalog, and images to extract hidden relations and features.
• Conduct research to explore ongoing cutting-edge ML techniques (especially deep learning) and conduct a quick POC.
• Work closely with Data Engineers and Senior Data Scientists to integrate and scale ML components to a production-level that can handle terabytes of data.
• Continuously learn and stay up to date with the current state-of-the-art techniques by reading research papers and attending AI/ML conferences.
• Own deep data analysis and A/B test debugging, proactively identifying root causes, assessing impact, and providing clear, data-driven direction on next steps (e.g., what to fix and how to adjust experiment design).

Qualifications:

• BS/MS degree in Computer Science or a related discipline with a strong mathematical foundation and excellent programming skills (primarily Python)
• 8+ years experience building ML-driven fast and scalable ML/analytical algorithms in a corporate/startup environment.
• Strong awareness and understanding of recent trends in Generative AI and LLMs. Experience in working with GenAI stack will be treated as strong credentials.
• Strong understanding of various machine learning and natural language processing technologies, such as classification, information retrieval, clustering, knowledge graph, semi-supervised learning and ranking.
• Excellent exploratory data analysis skills with the ability to slice and dice data at scale using SQL in Redshift/BigQuery.
• Good problem solving and analytical skills. Ability to learn and adapt to newer ML technologies.
• Exposure to deep learning stack (PyTorch/Keras/TensorFlow) and techniques (Representation/Transfer Learning, RNN/LSTM, Transformers).
• Experience working with Big Data in a cloud based production environment (AWS/GCP/Azure).
• Effective communication skill in English, both verbally and in written form.

See yourself at Twilio

Join the team as Twilio’s next Senior Engineering Manager - Trust Intelligence Platform

About the job

The Traffic Intelligence organization at Twilio establishes trusted communications, ensuring that every interaction is safe, wanted and legal. This position is needed to build advanced machine learning models and robust data pipelines that enable fast, accurate risk predictions and decisions at scale across all communication channels including messaging, voice, email. The engineering team leads systems that are highly scalable and determines if the communications are legal; and wanted in near real time or prior to the communications being sent from the platform. This role requires a blend of technical depth in distributed systems and a strategic mindset to partner with Product and Engineering leaders to execute an AI/ML roadmap.This role interfaces with several key stakeholders and works on initiatives that are tracked at the executive level. 

Responsibilities

In this role, you’ll:

• Manage and Mentor a team of talented Machine Learning and Data Engineers with various levels of experience and positively influencing their careers.
• Partner with Product Managers and Architects to distill customer needs into actionable technical requirements and long-term roadmaps.
• Ensure best engineering practices & oversee end-to-end execution of large-scale ML solutions with operational excellence. 
• Work with data platform teams to build robust, scalable batch and real-time data pipelines.
• Work closely with the Fraud and Compliance  Operations team and the Data Analytics team to identify and understand the ever-changing landscape of fraud vectors and then take action to keep up with new forms of fraud.
• Work with other product and development teams to ensure that Twilio’s new and existing products incorporate anti-fraud efforts and publish the appropriate data to our fraud-fighting tools.
• Advocate for agile processes, continuous integration (CI/CD), automated testing, and sophisticated model monitoring to minimize "toil."
• Institute and maintain a rotating on-call incident escalation and response processes for the team.
• Manage highly critical risk platform tools in the cloud.
• Own reliability for the team’s services and participate in an on-call rotation.
• Adapt to prioritizing multiple issues in a high-pressure environment.
• Understand complex architectures and be comfortable working with multiple teams.
• Conduct short term and long term planning to achieve team’s goals identifying both tactical and strategic commitments and gaps while performing capacity management and ruthless prioritization. 

Qualifications 

Not all applicants will have skills that match a job description exactly. Twilio values diverse experiences in other industries, and we encourage everyone who meets the required qualifications to apply. While having “desired” qualifications make for a strong candidate, we encourage applicants with alternative experiences to also apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

Required:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 10–14+ years of total experience in machine learning /data engineering.
  5+ years of experience leading and managing engineering teams.
• Proven track record of shipping and maintaining ML models in a fast-paced, production environment.
• Experience developing highly-available full stack applications and distributed systems
• Stellar communication, organization and management skills with proven track record in an agile environment.
• Ability to explain your technical and business decisions succinctly as well as in detail.
• Languages: Expert proficiency in Python. Familiarity with Java or Scala is a plus.
• ML Frameworks: Deep experience with PyTorch, TensorFlow, or Keras.
• Data Tools: Experience with Kafka, Apache Spark, Hadoop, Presto, and DynamoDB.
• Cloud Platforms: Significant experience with AWS (specifically SageMaker, EKS, or ECS).
• Observability: Familiarity with tools like Datadog and Grafana.

Desired:

• Experience working in fraud/compliance domain.
• Knowledge of telecommunications.
• Familiarity with popular LLMs and latest developments. 

Location

This role will be remote, but is not eligible to be hired in CA, CT, NJ, NY, PA, WA.

Travel 

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.

What We Offer

There are many benefits to working at Twilio, including, in addition to competitive pay, things like generous time-off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

Compensation

*Please note the salary range information provided applies only to candidates residing in California, Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Washington D.C., and Washington State due to local requirements. Compensation for candidates in other locations will be discussed during the hiring process. Please note that hiring for this role is not restricted to the locations listed above.

The estimated pay ranges for this role are as follows:

• Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C. : $207,200 - $259,000.
• Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $219,360 - $274,200.
• Based in the San Francisco Bay area, California: $243,680 - $304,600.
• This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan. All roles are generally eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave.

The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location.

Applications for this role are intended to be accepted until May 21st, 2026, but may change based on business needs. 

Senior Vision AI Engineer 
(Cognitive Vision and Industrial AI)

Location: Mid-Atlantic Region
Company: Linque
Reports to: Head of Vision AI

About Proconex

Proconex is a trusted leader in industrial automation and process control solutions, proudly serving the industry for over 75 years. With a rich legacy of delivering high-performance systems and equipment to process industries—including oil & gas, chemicals, power, and life sciences—we are now entering an exciting new chapter.

We are  building on a solid foundation of over 10 years of successful deployments with our next generation of software products. Our software solutions are designed to empower industrial operators with operational analytics, enabling smarter, more efficient, and more reliable operations. This is a unique opportunity to be part of a growth-focused team that is taking proven technology to the next level.

About the Role

Linque is expanding its Vision AI and Cognitive Automation platform focused on applying real-time computer vision and AI to industrial, biopharmaceutical, and process manufacturing environments. We are seeking a Senior Vision AI Engineer to help lead the development, deployment, and customer-facing application of advanced vision AI solutions. This role sits at the intersection of deep technical execution, platform development, and real-world industrial use cases.

Key Responsibilities

• Design, develop, and deploy production-grade computer vision and machine learning models
• Build optimized end-to-end vision pipelines for real-time and near-real-time applications
• Translate complex industrial problems into scalable AI architecture
• Collaborate cross-functionally with product, engineering, and commercial teams
• Participate in technical customer discussions, pilots, and evaluations
• Support prototypes through pilot and production transitions
• Mentor junior engineers and contribute to technical best practices

Required Qualifications

• 5+ years’ experience in computer vision and machine learning
• Strong hands-on experience deploying AI systems in production
• Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, Keras)
• Deep knowledge of Video / Image processing tools (e.g. Mask R-CNN, ResNet, U-Net)
• Knowledge of object and anomaly detection (Autoencoders, FastFlow, Transformers)
• Tunning experience for CNNs and Vision Models (e.g., MLFlow, NVIDIA TAO, MMD, MMS)
• Mastery of model interchange and GPU acceleration (e.g. ONNX, CUDA, cuDNN)
• Experience working with image/video pipelines, container orchestration (local and cloud)
• Understanding of the full ML / AI lifecycle

Preferred Qualifications

• Experience with real-time vision systems
• Background in industrial automation or regulated environments
• Experience with edge or cloud deployment
• Ability to communicate complex technical topics clearly

Why Join Linque

• Apply AI to real industrial problems with measurable impact
• Collaborate with experienced AI and industrial leaders
• Influence the evolution of next-generation Vision AI platforms
• Flexible, growth-oriented environment

Apply today to learn more about this exciting new opportunity at Proconex, the exclusive Emerson Impact Partner for the Mid-Atlantic region!

Summary:
Tekion seeks an exceptionally talented and seasoned Senior Staff Applied Scientist to architect the future of our AI-driven solutions. The incumbent will assume a pivotal role in our organization, providing the strategic and technical stewardship necessary to translate cutting-edge research into tangible business value. The ideal candidate is a first-principles thinker, adept at navigating ambiguity, and possesses the intellectual curiosity to formulate and solve complex, unstructured problems. This is a seminal opportunity to influence the trajectory of our AI strategy and deliver transformative solutions at an enterprise scale. 

Key Responsibilities:

• Strategic Direction: Architect and execute the strategic vision for applied AI and Machine Learning within Tekion, ensuring rigorous alignment with overarching business objectives and industry challenges.
• Innovation & Research Leadership: Steer the R&D roadmap by identifying and capitalizing on emergent technological opportunities. Drive innovation through the ideation and implementation of novel, scientifically-grounded solutions.
• Stakeholder Alignment: Serve as the principal technical liaison between the R&D organization and executive stakeholders, ensuring technical strategies are congruent with business imperatives.
• Cross-Functional Execution: Lead collaborations with product, engineering, and business units to define, develop, and integrate sophisticated machine learning systems into core products and services.
• Scientific Contribution: Contribute to the broader scientific community through publications in premier academic conferences and journals, enhancing Tekion's position as a center of innovation.
• Mentorship & Talent Development: Mentor and cultivate a culture of scientific rigor and innovation among applied scientists, guiding project execution and fostering professional growth.
• Impact Quantification: Establish robust frameworks for model evaluation and performance measurement. Quantify and articulate the business impact of machine learning initiatives to executive leadership.
• Governance & Best Practices: Institute and govern best practices for the entire machine learning lifecycle, including model development, validation, deployment, and monitoring, while championing ethical and responsible AI

Core Competencies & Technical Expertise
The successful candidate will demonstrate mastery in the following areas:

• Foundational Expertise: Deep, theoretical and practical expertise in Machine Learning, Deep Learning, Causal Inference, and Explainable AI.
• Statistical Rigor: Advanced proficiency in applied probability and statistics to derive and validate insights from complex, high-dimensional data.
• Deep Learning:
  • Expert-level proficiency with frameworks such as TensorFlow, Keras, and PyTorch.
  • Extensive experience implementing advanced neural network architectures.
  • Practical application of Computer Vision (e.g., OpenCV) and Natural Language Processing (e.g., spaCy) methodologies.
• Large Language Models (LLMs): Demonstrated experience with Large Language Models, including advanced prompt engineering, fine-tuning, and deployment for specific business applications.
• Technical Proficiencies:
  • Advanced programming skills in Python and mastery of SQL. Familiarity with distributed computing frameworks (e.g., Spark) is advantageous.
  • Proficiency with cloud computing platforms (GCP, Azure, AWS).
  • Expertise in experimental design (A/B testing, causal inference).
  • Proficient in version control systems (Git).

Required Qualifications

• An advanced degree (Ph.D. or M.S. preferred) in a quantitative discipline such as Computer Science, Statistics, Operations Research, Physics, or a related field.
• A minimum of 10+ years of post-academic experience in applied science or quantitative research roles, with a demonstrable history of translating complex models into tangible business value.
• A distinguished track record of solving difficult, business-critical problems using a scientific, data-driven approach.
• Proven experience in programming, data manipulation, and building models in a business context.
• Sophisticated data visualization and presentation skills, with the ability to distill complex analytical results into clear, actionable insights for diverse audiences.

Ideal Candidate Profile

• A profound intellectual curiosity and a systematic, first-principles approach to problem-solving.
• Domain expertise in the automotive industry or related fields such as finance or enterprise SaaS is highly desirable.
• Experience in specialized areas such as Recommendation Engines or advanced NLP is preferred.
• Exceptional communication and presentation capabilities, with a proven ability to distill complex technical concepts for executive-level audiences.
• A demonstrated ability to work collaboratively and effectively lead initiatives across multi-disciplinary teams.
• A commitment to continuous personal and team development within a collaborative, high-performance culture.

Address:

Bangalore Office  

Tekion India Private Limited 

6th, 7th & 8th Floor, Helium, Bagmane Solarium City, Doddanekkundi Village, KR Puram Hobli, East Taluk, Bangalore - 560037 

Chennai Office

Embassy Splendid Zone, Block 2, 9th floor, Velan Nagar, Arulmurugan Nagar, Old Pallavaram, Chennai, Tamil Nadu 600043

ABOUT THE ROLE

You are a seasoned Data Scientist, passionate about building robust, real-time machine learning solutions to combat financial crime. Working within the Risk & Fraud Team, you will leverage advanced statistical modeling and machine learning to detect, prevent, and adapt to evolving fraud threats. You thrive on solving complex problems with highly imbalanced data and delivering tangible risk reduction impact in a fast-paced environment.

You strongly believe in agile principles and use them to deliver value incrementally. You are eager to learn about new methodologies and practices and apply them directly in your work.

As a Senior Data Scientist you’ll be:

• Model Development & Risk Mitigation: Design, develop, and implement advanced ML/Statistical models to predict and prevent various fraud typologies. Focus on driving impact by optimising costs and reducing risk using ML/Stats models.
• Specialised Data Handling: Employ advanced techniques to manage and model highly imbalanced, large datasets characteristic of the fraud domain.
• Adaptive Systems: Build and maintain models that can quickly adapt to new and evolving fraud typologies and emerging threats.
• Real-Time MLOps: Develop, optimise, and deploy ML models for real-time/low-latency inference in production settings.
• Data & Feature Engineering: Utilize, enrich, and contribute to the feature store ecosystem, ensuring high-quality, scalable features for risk models.
• Performance Monitoring: Implement and maintain robust drift monitoring and model performance tracking to ensure deployed models remain effective and stable.
• Collaboration: Work closely with ML Engineers to productionize models leveraging AWS/GCP tech stack, and collaborate with Business and Product teams to understand requirements and solutionise data products.
• Exploration: Identify creative solutions in order to build relevant training data sets and explore the value of new data structures like knowledge graphs for relational fraud detection.

WHAT ARE WE LOOKING FOR

• You have 6+ years of experience in Software Development or Machine Learning, with a strong emphasis on practical model development and deployment.
• You are Strong in Python and have expert knowledge with Machine Learning tools/libraries (e.g., scikit-learn, statmodels, TensorFlow, Keras, or PyTorch).
• You have experience with big-data technologies such as Spark, SparkML, Hadoop etc. and have handled large data in a distributed processing environment. AWS, GCP, or Azure (anyone) cloud knowledge is preferred.
• You are proficient in ML training, optimising, feature selection and engineering, hyperparameter tuning and have knowledge about trade-offs in using different algorithms.
• You have demonstrated experience in developing and deploying a variety of ML-algorithms (e.g., logistic regressions, boosted trees, neural networks) that work in real-time settings.
• You have a good working knowledge with basic data table operations (SQL etc.), and data transform in the warehouse (dbt etc.).
• You are comfortable with ambiguity and are a self-starter—you take initiative in spotting opportunities and finding ways to solve challenges with data.
• Familiarity with Financial Services and Fintech space is preferred.
• You will be helping optimise all aspects of our sales funnel including finding ways to increase lead quality, reduce our cost of acquisition, optimise lead allocation, and improve the likelihood of successful lending outcomes for our members

Highly Desirable Skills:

• Exposure to Cost-Sensitive Learning techniques, where the economic impact of prediction errors is a key optimization factor.
• A decent idea and practical exposure to MLOps principles (e.g., model versioning, continuous integration/deployment for ML).
• Experience with Drift monitoring tools and frameworks.
• Exposure to Knowledge Graphs or graph database applications.

• Competitive Compensation -  competitive salary and share options
• Time Off – Generous annual leave on top of bank holidays.
• Parental Leave – Paid maternity, paternity, and adoption leave to support your family journey.
• Sabbatical – Extended unpaid and paid leave options after completing milestone years with Tide.
• Health Insurance – Private family insurance with additional OPD coverage and top-up options.
• Life & Accident Cover – Comprehensive accidental and life insurance protection.
• Mental Wellbeing – Access to therapy sessions, courses, meditations, and workshops.
• Volunteering & Development Days – Paid days annually for volunteering or personal growth.
• Learning & Development – Annual budget for books, courses, coaching, and more.
• WOO (Work Outside the Office) – Work from abroad for up to 90 days annually.
• Home Office Setup – Contribution towards setting up your home office
• Laptop Ownership – Keep your old laptop and get a new one when it’s time for a replacement.
• Snacks & Meals – Office perks with snacks, coffee, tea, and lunch (location dependent).

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

ABOUT THE ROLE

You are a seasoned Data Scientist, passionate about building robust, real-time machine learning solutions to combat financial crime. Working within the Risk & Fraud Team, you will leverage advanced statistical modeling and machine learning to detect, prevent, and adapt to evolving fraud threats. You thrive on solving complex problems with highly imbalanced data and delivering tangible risk reduction impact in a fast-paced environment.

You strongly believe in agile principles and use them to deliver value incrementally. You are eager to learn about new methodologies and practices and apply them directly in your work.

As a Senior Data Scientist you’ll be:

• Model Development & Risk Mitigation: Design, develop, and implement advanced ML/Statistical models to predict and prevent various fraud typologies. Focus on driving impact by optimising costs and reducing risk using ML/Stats models.
• Specialised Data Handling: Employ advanced techniques to manage and model highly imbalanced, large datasets characteristic of the fraud domain.
• Adaptive Systems: Build and maintain models that can quickly adapt to new and evolving fraud typologies and emerging threats.
• Real-Time MLOps: Develop, optimise, and deploy ML models for real-time/low-latency inference in production settings.
• Data & Feature Engineering: Utilize, enrich, and contribute to the feature store ecosystem, ensuring high-quality, scalable features for risk models.
• Performance Monitoring: Implement and maintain robust drift monitoring and model performance tracking to ensure deployed models remain effective and stable.
• Collaboration: Work closely with ML Engineers to productionize models leveraging AWS/GCP tech stack, and collaborate with Business and Product teams to understand requirements and solutionise data products.
• Exploration: Identify creative solutions in order to build relevant training data sets and explore the value of new data structures like knowledge graphs for relational fraud detection.

WHAT ARE WE LOOKING FOR

• You have 6+ years of experience in Software Development or Machine Learning, with a strong emphasis on practical model development and deployment.
• You are Strong in Python and have expert knowledge with Machine Learning tools/libraries (e.g., scikit-learn, statmodels, TensorFlow, Keras, or PyTorch).
• You have experience with big-data technologies such as Spark, SparkML, Hadoop etc. and have handled large data in a distributed processing environment. AWS, GCP, or Azure (anyone) cloud knowledge is preferred.
• You are proficient in ML training, optimising, feature selection and engineering, hyperparameter tuning and have knowledge about trade-offs in using different algorithms.
• You have demonstrated experience in developing and deploying a variety of ML-algorithms (e.g., logistic regressions, boosted trees, neural networks) that work in real-time settings.
• You have a good working knowledge with basic data table operations (SQL etc.), and data transform in the warehouse (dbt etc.).
• You are comfortable with ambiguity and are a self-starter—you take initiative in spotting opportunities and finding ways to solve challenges with data.
• Familiarity with Financial Services and Fintech space is preferred.
• You will be helping optimise all aspects of our sales funnel including finding ways to increase lead quality, reduce our cost of acquisition, optimise lead allocation, and improve the likelihood of successful lending outcomes for our members

Highly Desirable Skills:

• Exposure to Cost-Sensitive Learning techniques, where the economic impact of prediction errors is a key optimization factor.
• A decent idea and practical exposure to MLOps principles (e.g., model versioning, continuous integration/deployment for ML).
• Experience with Drift monitoring tools and frameworks.
• Exposure to Knowledge Graphs or graph database applications.

• Competitive Compensation -  competitive salary and share options
• Time Off – Generous annual leave on top of bank holidays.
• Parental Leave – Paid maternity, paternity, and adoption leave to support your family journey.
• Sabbatical – Extended unpaid and paid leave options after completing milestone years with Tide.
• Health Insurance – Private family insurance with additional OPD coverage and top-up options.
• Life & Accident Cover – Comprehensive accidental and life insurance protection.
• Mental Wellbeing – Access to therapy sessions, courses, meditations, and workshops.
• Volunteering & Development Days – Paid days annually for volunteering or personal growth.
• Learning & Development – Annual budget for books, courses, coaching, and more.
• WOO (Work Outside the Office) – Work from abroad for up to 90 days annually.
• Home Office Setup – Contribution towards setting up your home office
• Laptop Ownership – Keep your old laptop and get a new one when it’s time for a replacement.
• Snacks & Meals – Office perks with snacks, coffee, tea, and lunch (location dependent).

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

About WPP Media  

WPP is the trusted growth partner for the world’s leading brands. With exceptional talent, trusted data and intelligence, and world-class partnerships – all united by our pioneering agentic marketing platform, WPP Open – we help clients navigate change, capture opportunity, and deliver transformational growth.   

WPP Media is WPP's AI-driven media operating unit, bringing together media, data, and partnerships to deliver creative personalisation at scale. Connected through WPP Open and powered by Open Intelligence, clients see exactly where, how, and why their media investment is working.  

For more information, visit wppmedia.com. 

 Role Summary and Impact 

The Media Futures Group AI Squad is a small, agile, and autonomous innovation team dedicated to charting the course for AI transformation across APAC for one of WPP’s most important and strategic global technology clients. 
 
By seamlessly integrating AI across media, creative, and production, this cross-functional squad delivers cutting-edge innovation and pioneering work to deliver more effective and efficient business outcomes. 
 
The team’s mission is to solve specific business challenges by delivering demonstrable proof of AI-enabled marketing improvements, providing strategic guideposts for the broader organization. 
 
Utilizing best-in-class tools like WPP Open and Gemini, you will innovate and deliver award-winning creative ideas while building, testing, and scaling solutions that enhance effectiveness, efficiency, and execution for our clients. 

 The AI Solutions Engineer serves as the master builder executing the construction. This highly technical role provides the dedicated, hands-on development support required to forcefully move theoretical architectural visions out of isolated testing environments and into highly secure, Google-approved, enterprise-grade production infrastructures. The AI Solutions Engineer bridges the critical, often perilous gap between a fragile, locally hosted prototype and a highly scalable, robust organizational tool capable of withstanding massive global traffic. 

Responsibilities 

• API & UI Development: Construct complex backend Application Programming Interface (API) connections and develop the secure user interfaces absolutely necessary to bridge the proprietary WPP Open platform with localized campaign tools and highly guarded client data lakes. 

• Live Deployment & Debugging: Execute rapid debugging, performance analysis, and troubleshooting of both machine learning models and underlying cloud infrastructure in real-time to prevent catastrophic performance degradation or service outages during live campaign sprints. 

• Security & Compliance: Strictly document the deployed technical architecture upon the conclusion of active campaigns. Solidify security protocols and data pipelines to ensure absolute compliance with enterprise risk standards and global data privacy regulations. 

• Codebase Handover: Facilitate the seamless handover of the finalized codebase to centralized, operations-driven technology teams, ensuring pristine code quality, proper containerization, and long-term deployment readiness. 

Skills and Experience 

• A minimum of 5 years of applied experience in software engineering, highly technical support, or complex solutions engineering. 

• At least 2 years focused exclusively on deploying machine learning (ML) or natural language processing (NLP) applications in live commercial environments. 

• Exceptional coding and scripting capabilities, primarily utilizing Python, Java, C++, or Go. 

• Deep, academic understanding of data structures, complex algorithms, and object-oriented software design principles. 

• Proven, hands-on experience troubleshooting, debugging, and reproducing obscure issues within advanced machine learning frameworks, specifically TensorFlow, Keras, and PyTorch. 

• Extensive operational experience navigating public cloud services, specifically Google Cloud Platform (GCP) components such as Kubernetes, Compute Engine, and Apache Beam. 

• Thorough understanding of computer networking, peering with private clouds, managing highly distributed systems, and Git version control. 

Key Competencies 

• Vertex MLOps & Cloud Infrastructure Deployment: Capable of establishing robust, automated machine learning pipelines using Vertex AI Pipelines and Google Cloud Platform components like Kubernetes and Compute Engine. Must ensure that generative AI tools are properly containerized to scale securely and withstand massive global traffic during live campaigns. 

• Vertex AI Mastery: Deep, hands-on proficiency with Google Cloud's Vertex AI platform as the exclusive, mandated environment for model deployment. Capable of navigating the Vertex Model Garden, configuring foundational models (like Gemini), and executing parameter-efficient fine-tuning for specific campaign needs 

• Secure RAG & Grounding Pipeline Engineering: Expert ability to build complex Retrieval-Augmented Generation (RAG) architectures within Vertex AI. Must demonstrate high technical acumen in securely connecting generative models to highly guarded, proprietary enterprise data lakes and Customer Data Platforms without exposing PII or violating data governance. 

• Rapid Problem-Solving: Ability to diagnose and repair code-level pipeline failures or UI breakdowns under the extreme pressure of a live campaign sprint. 

• Extreme Psychological Resilience: Thriving in highly volatile, fast-paced deployment environments where prototype code must be hardened instantly. 

Life at WPP Media & Benefits  

Our passion for shaping the next era of media is powered by our commitment to Be Extraordinary, investing in our employees to inspire transformational creativity. We also Lead Optimistically, firmly believing in and Championing Growth and Development for every individual. This commitment allows WPP Media employees to leverage the extensive global WPP Media & WPP networks to pursue their passions, build vital professional connections, and learn at the cutting edge of marketing and advertising.  

We Create an Open environment built on trust and respect, where everyone feels they belong and has opportunities to progress. This inclusive culture is fostered through a variety of employee resource groups and frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our comprehensive benefits package reflects this commitment, including competitive medical, vision, and dental insurance, significant paid time off, preferential partner discounts, and employee mental health awareness days.    

WPP Media is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We believe the best work happens when we're together, fostering creativity, collaboration, and connection in this open and supportive environment. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process.  

Please note that while our philosophy is the same across WPP, benefits may vary by office/country. 

#LI-Regional

WHAT YOU'LL DO

Our Data Scientist, AI Deployment team is a group of creative technical experts who design and build end-to-end machine learning solutions that power 1-to-1 personalization for some of the world's leading brands. In this role, you will:

• Design ML use cases from the ground up — scoping solutions that optimize for real business value, accounting for the complexity of modern marketing journeys, and proactively identifying risks to set each engagement up for success
• Build and own the full ML pipeline —  taking customers' raw data through transformation, model training, and activation, so that model decisions are delivered to personalize experiences for millions of end users
• Drive customer success by providing ongoing technical guidance that ensures data science performance, successful adoption, and measurable outcomes
• Extend product capabilities by developing features and tools that support the broader AI deployment team and scale what's possible across engagements
• Partner with the Braze Product team to refine and advance Braze's reinforcement learning algorithms, pushing the self-learning capabilities of the platform forward
• Shape BrazeAI product strategy and roadmap by bringing customer-facing insights and deep technical expertise to the table

WHO YOU ARE

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
• Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
• Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
• Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences

For candidates based in Ontario, the pay range at the start of employment for this position is expected to be between CA$112,000 - CA$168,000/year, with an expected On Target Earnings (OTE) between CA$125,000 - CA$188,000/year (including performance-based or variable compensation (bonus or commission). Your particular offer may vary depending on multiple individual factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

#LI-Hybrid

Your Impact

We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a key member of our research and development efforts, you will play a crucial role in advancing the state-of-the-art in Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), Computer Vision and GenAI technologies for law enforcement and beyond. You will collaborate with cross-functional teams to design, develop, and deploy cutting-edge LLM, MLLM, CV models and algorithms and solutions that enable intelligent reasoning, perception and understanding of multimodal data.

What You’ll Do
Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see https://www.axon.com/company)

• US: Seattle, Boston, Scottsdale

Responsibilities

• Own one or more key technical areas across LLM, MLLM, CV product portfolio.
• Provide technical leadership to junior scientists, guiding the transition of R&D concepts into impactful Axon product feature.
• Research and develop cutting-edge techniques in LLM, MLLMs, GenAI, and Computer Vision across cloud, devices and sensors based data sources.
• Design and implement efficient and scalable MLLM models for inference and analysis of multimodal data.
• Explore novel approaches to address challenges in NLP, NLU, Object Detection, Object Recognition, Object Tracking, Segmentation, and Scene Understanding.
• Optimize AI models, algorithms for performance, memory footprint, and energy efficiency to meet the requirements of resource-constrained devices.
• Join force with MLEs or firmware or hardware engineers to leverage hardware accelerators and optimize algorithms for specific hardware architectures.
• Evaluate the performance of LLM, MLLM, CV models using real-world datasets and design experiments to validate their effectiveness.
• Stay up-to-date with the latest research trends and advancements in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant findings into our projects.
• Contribute to patent disclosures, academic publications, and technical documentation to share insights and findings with the broader community.
• Experience coach and mentor junior scientists.

What You Bring

• PhD and with +5 years for ML Scientist, +8 years for Sr. ML Scientist, +10 years for Principal ML Scientist experience in Computer Science or a related field with a focus on LLM, MLLMs, Computer Vision, GenAI.
• Proven track record of research excellence in LLM, MLLM, Computer Vision, Robotics Perception, GenAI, demonstrated through publications in top-tier conferences or journals.
• Strong proficiency in programming languages such as Python, C/C++, experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras and experience with ROS or robotic operational system.
• Drive one or more phases of the ML development lifecycle: shape datasets, investigate modeling approaches and architectures, train/evaluate/tune models and implement the end-to-end training pipeline.
• Leverage state-of-the-art research to deliver high quality models enabling multiple AI projects at scale.
• Contribute back to the research community via academic publications, tech blogs, open-source code and contributing to internal/external AI challenges
• Experience in developing computer vision algorithms for resource-constrained devices such as mobile phones, IoT devices, or embedded systems is highly desirable.
• Excellent problem-solving skills, analytical thinking, and the ability to work independently as well as collaboratively in a team environment.
• Strong communication skills and the ability to effectively present complex technical concepts to both technical and non-technical audiences.

Benefits that Benefit You

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Medical, Dental, Vision plans
• Fitness Programs
• Emotional & Mental Wellness support
• Learning & Development programs
• And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work

Location: This role is based out of our Boston, MA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesday through Friday, with flexibility to work remotely on Mondays. We believe connection fuels innovation, and our in-office culture is designed to support meaningful teamwork and mentorship.

Your Impact

We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a key member of our research and development efforts, you will play a crucial role in advancing the state-of-the-art in Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), Computer Vision and GenAI technologies for law enforcement and beyond. You will collaborate with cross-functional teams to design, develop, and deploy cutting-edge LLM, MLLM, CV models and algorithms and solutions that enable intelligent reasoning, perception and understanding of multimodal data.

What You’ll Do
Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see https://www.axon.com/company)

• US: Seattle, Boston, Scottsdale

Responsibilities

• Own one or more key technical areas across LLM, MLLM, CV product portfolio.
• Provide technical leadership to junior scientists, guiding the transition of R&D concepts into impactful Axon product feature.
• Research and develop cutting-edge techniques in LLM, MLLMs, GenAI, and Computer Vision across cloud, devices and sensors based data sources.
• Design and implement efficient and scalable MLLM models for inference and analysis of multimodal data.
• Explore novel approaches to address challenges in NLP, NLU, Object Detection, Object Recognition, Object Tracking, Segmentation, and Scene Understanding.
• Optimize AI models, algorithms for performance, memory footprint, and energy efficiency to meet the requirements of resource-constrained devices.
• Join force with MLEs or firmware or hardware engineers to leverage hardware accelerators and optimize algorithms for specific hardware architectures.
• Evaluate the performance of LLM, MLLM, CV models using real-world datasets and design experiments to validate their effectiveness.
• Stay up-to-date with the latest research trends and advancements in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant findings into our projects.
• Contribute to patent disclosures, academic publications, and technical documentation to share insights and findings with the broader community.
• Experience coach and mentor junior scientists.

What You Bring

• PhD and with +5 years for ML Scientist, +8 years for Sr. ML Scientist, +10 years for Principal ML Scientist experience in Computer Science or a related field with a focus on LLM, MLLMs, Computer Vision, GenAI.
• Proven track record of research excellence in LLM, MLLM, Computer Vision, Robotics Perception, GenAI, demonstrated through publications in top-tier conferences or journals.
• Strong proficiency in programming languages such as Python, C/C++, experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras and experience with ROS or robotic operational system.
• Drive one or more phases of the ML development lifecycle: shape datasets, investigate modeling approaches and architectures, train/evaluate/tune models and implement the end-to-end training pipeline.
• Leverage state-of-the-art research to deliver high quality models enabling multiple AI projects at scale.
• Contribute back to the research community via academic publications, tech blogs, open-source code and contributing to internal/external AI challenges
• Experience in developing computer vision algorithms for resource-constrained devices such as mobile phones, IoT devices, or embedded systems is highly desirable.
• Excellent problem-solving skills, analytical thinking, and the ability to work independently as well as collaboratively in a team environment.
• Strong communication skills and the ability to effectively present complex technical concepts to both technical and non-technical audiences.

Benefits that Benefit You

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Medical, Dental, Vision plans
• Fitness Programs
• Emotional & Mental Wellness support
• Learning & Development programs
• And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work

Location: This role is based out of our Seattle, WA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesday through Friday, with flexibility to work remotely on Mondays. We believe connection fuels innovation, and our in-office culture is designed to support meaningful teamwork and mentorship.

ABOUT THIS OPPORTUNITY

onX is seeking a Staff Software Engineer who will contribute to meaningful, real-world outcomes that have a lasting impact for customers and the business. In this role, you’ll focus on the design, development, and scaling of our core AI/ML platforms and product-facing services as part of the AI Foundations Team, supporting the integration of cutting-edge artificial intelligence solutions across onX's product lines. You’ll take ownership of your work, collaborate closely with partners across the organization, and help move initiatives forward in an environment where priorities evolve, learning is celebrated, and you’re encouraged to keep stretching your skills. This role will report to the Director of Engineering.

WHAT YOU'LL DO
^{Essential Job Duties & Functions}

• Work on the design, development, and deployment of large-scale AI systems and services, including models, pipelines, product experiences and infrastructure.
• Help Drive the technical strategy and roadmap for AI feature development, focusing on scalability, repeatability, reliability, and performance.
• Mentor and guide other engineers in best practices and productionizing AI technologies.
• Collaborate with Product and Data Science teams to translate business problems into technical requirements and deliver high-impact AI solutions (combining LLMs, Vector Databases, ML and other technology in novel ways to serve onX’ unique audience).
• Look for opportunities to embed AI as a repeatable mechanism in daily workflows by integrating experimentation into real work, and continuously refining its use with sound judgment and validation.
• Be a leader in AI safety, ensuring AI-enabled products are aligned with our values and mission.
• Look for opportunities to embed AI as a repeatable co-pilot in daily workflows by integrating experimentation into real work, and continuously refining its use with sound judgment and validation.

WHAT YOU’LL BRING

• Bachelor’s degree in Computer Science, Data Science, or a related technical field, or equivalent experience.
• 10+ years of professional software engineering experience, with at least 3 years focused on building and scaling production AI/ML systems, is required.
• Expertise in building scalable backend systems.
• Deep knowledge of MLOps practices, cloud infrastructure (AWS/GCP/Azure), and CI/CD pipelines for machine learning models and the common inference APIs/SDKs and frameworks.
• Experience with modern AI technologies, including Large Language Models (LLMs) and their various architectures, methods such as RAG, vector databases, and the common AI stack including TensorFlow/Keras, PyTorch, Transformers, etc.
• A strong curiosity for exploring new technologies, including AI
• A shared passion for and ability to demonstrate onX’s Company Values.
• Permanent US work authorization is a condition of employment with onX.

ADDED BONUSES

Though not required, we would be thrilled to consider candidates with any of the following:

• A history of engaging in AI development, from the early ML/NN (YOLO, Darknet) to the LLM era.
• Experience in monitoring and debugging production AI systems (inference, evals, judging, benchmarks) including cost and performance optimizations.
• Interest or experience in edge/on-device inference (MLX, JAX, transformers on TPU/NPU, etc.)
• Interest, experience or experimentation in training/fine-tuning transformer/diffusion models, dataset curation and captioning, etc.

THE ONX EXPERIENCE

onX is a distributed company with more than 400 employees across the country. We come together regularly to work in person and stay connected through regional basecamps and a culture that balances individual ownership with deep collaboration.

While we move quickly, we’re not a scrappy start-up. We operate with clear goals, structure, and frameworks that guide how we prioritize and execute. Priorities matter. While they may shift, data shapes how we evolve as our business, products, and the world around us change.

Clear priorities and structure don’t limit ownership - they make it possible. You’ll have the autonomy to define your work and make meaningful decisions within clear strategic boundaries. You’ll partner closely with others to solve complex problems and build solutions that scale across teams and platforms. Along the way, you’ll be supported with feedback, tools, and opportunities to grow your craft as you take on new challenges.

WHERE YOU CAN WORK

onX has created a thriving distributed workforce designed to foster connection, collaboration, and shared experience across several US locations. We have two HQ locations in Bozeman and Missoula, MT and established virtual workforce Basecamps in Austin, TX; Denver, CO; Kalispell, MT; Minneapolis, MN; Portland, OR; Salt Lake City, UT; and Seattle, WA.

HOW YOU’LL BE COMPENSATED

onX is committed to compensating all employees fairly and equitably for their contributions.  Applicants can expect to make between $169,000 to $211,000 upon hire. The pay range will vary based on experience, skills, certifications, and education among other factors as required in the job description. In addition, full-time onX employees are eligible for a grant of common share options with a vesting schedule and a potential annual bonus of 10% based on company performance.

WHAT WE’RE OFFERING YOU

• Competitive salaries, annual bonuses, equity, and opportunities for growth
• Comprehensive health benefits, including a no-monthly-cost medical plan
• Paid parental leave of 13 weeks for birthing parents and 5 weeks for non-birthing parents
• 401k matching at 100% for the first 3% you save and 50% from 3-5%
• Company-wide outdoor adventures and amazing outdoor industry perks
• Annual “Get Out, Get Active” funds to fuel your active lifestyle
• Flexible time away package that includes PTO, STO, VTO, and paid holidays

PERFORMANCE ESSENTIALS

In this role, success is driven by cognitive abilities such as concentration and problem-solving, essential for our computer-centric tasks. onX will explore reasonable accommodations to ensure that individuals with diverse abilities can fully engage in and contribute to the essential physical and mental functions of the job. If you need assistance or accommodation, please contact us at PC@onxmaps.com. 

Application Deadline is [day of week], [month] [day] at [0:00 pm] MST

Position open until filled. 

#LI-Remote

Perfil: Desarrollador Cloud

Rol: Desarrollador

Nivel: STD – SR

Experiencia

Años de experiencia:

• 3 o más años de experiencia como Desarrollador/a Cloud (Multi‑Nube) con IA/ML y DevOps.

Escolaridad

• Licenciatura o Ingeniería en:
• Sistemas
• Computación
• Matemáticas
• Física
• Carrera afín
• (O experiencia equivalente comprobable)

Modalidad y Condiciones de Trabajo

• Modalidad de trabajo: Híbrido
• Días en oficina: 2 veces por semana
• Horario: Lunes a viernes, 9:00 a.m. a 6:00 p.m.
• Ubicación: CDMX
• Dirección de sede: Polanco / Reforma

Objetivo del Puesto

Diseñar, construir y operar aplicaciones y servicios escalables en entornos multi‑nube (AWS, GCP y/o Azure), integrando desarrollo backend, prácticas DevOps/MLOps e implementación de modelos de IA/ML en entornos productivos, asegurando calidad, seguridad, observabilidad y eficiencia operativa.

Certificaciones Recomendadas

Google Cloud Platform

• Google Professional Cloud Developer
• Google Professional Cloud Architect (deseable para perfil SR)
• Google Professional Machine Learning Engineer
• Google Associate Cloud Engineer

Amazon Web Services (AWS)

• AWS Certified Developer – Associate
• AWS Certified Solutions Architect – Associate
• AWS Certified Machine Learning – Specialty (altamente alineada a IA/ML)
• AWS DevOps Engineer – Professional (deseable para perfil SR)

Microsoft Azure

• Microsoft Certified: Azure Developer Associate (AZ‑204)
• Microsoft Certified: Azure AI Engineer Associate
• Microsoft Certified: Azure DevOps Engineer Expert

Machine Learning

• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Azure Data Scientist Associate
• TensorFlow Developer Certificate
• IBM AI Engineering Professional Certificate

Idioma

• Inglés técnico (deseable)

Habilidades Blandas

• Trabajo en equipo
• Autogestión
• Perfil autodidacta
• Comunicación efectiva
• Resolución de problemas
• Adaptabilidad
• Proactividad
• Pensamiento analítico

Requisitos Técnicos

Versionador e Integrador de Código

• Git
• GitHub Actions / GitLab CI
• Cloud Build / Cloud Deploy (GCP)
• CodeBuild / CodePipeline (AWS)
• Azure DevOps Pipelines

Lenguajes de Programación

• Python
• Node.js
• TypeScript (deseable)
• SQL
• YAML (pipelines / Infraestructura como Código)

Sistemas Operativos

• Linux (principal)
• Windows
• macOS

Manejadores de Bases de Datos

• Cloud SQL
• Amazon RDS
• Azure SQL
• BigQuery
• Bases de datos relacionales y analíticas
• Almacenamiento de objetos:
• Amazon S3
• Google Cloud Storage
• Azure Blob Storage

Frameworks de Desarrollo

Backend

• Express
• Fastify (Node.js)

IA / ML

• scikit-learn
• TensorFlow / Keras
• PyTorch

NLP

• spaCy
• NLTK
• Hugging Face Transformers (deseable)

IDE

• Visual Studio Code
• IDEs compatibles con Python y Node.js

Herramientas

• Docker
• Kubernetes (GKE / EKS / AKS)
• Helm
• Terraform
• MLflow / DVC
• Postman (pruebas de APIs)
• Prometheus / Grafana
• OpenTelemetry

Plataformas Cloud

• Google Cloud Platform (principal)
• Amazon Web Services (deseable)
• Microsoft Azure (deseable)

Asistentes de IA

• No especificados explícitamente
• (Uso implícito de frameworks y plataformas de IA/ML)

Conocimiento del Negocio

Marcos o Metodologías de Trabajo

• Metodología Ágil
• Scrum

Herramientas para Seguimiento y Control de Proyectos

• Gestión de backlog (herramientas ágiles no especificadas)
• Métricas ágiles:
• Velocity
• Lead Time
• Tableros de observabilidad
• Definición y seguimiento de SLO / SLI

Esquema de Trabajo

• Asignación a proyectos
• Desarrollo y operación de productos digitales
• (No esquema de fábrica de software)

Tipo de Asignación

• Proyectos
• Operación
• Soporte productivo
• Mejora continua

Tipo de Proyecto

• Ágil

Industria

• Banca / Servicios Financieros

Tecnología

• Cloud Computing
• Inteligencia Artificial / Data

Location: Bucharest

About us:

IONOS is the largest cloud hoster in Europe and is setting up the foundation as European Cloud Provider. This includes not just offering storage that can compete with the American hyper-scalers, but that offers the full infrastructure stack, including AI & Machine Learning Products. As the largest hosting company in Europe, we manage more than 8 million customer contracts and host over 12 million domains in our own regional data centers in the US and Europe.

About the team:

The AI & ML Products Development department is responsible for building the platform for ML Services products for IONOS Cloud customers, as well as other companies in the United Internet group.

Our most recent product development features integration of GenerativeAI foundational models, LLMs and others. We run foundational models on prem in our cloud, such as Meta’s Llama, Mistral or StableDiffusion and also VectorDBs and offer them via APIs to our cloud customers.

We are also working with classic ML models for Computer Vision,  NLP), audio/voice  processing & predictions.

Our team is working with technologies such as HugginFace frameworks, TensorFlow, PyTorch, Keras, vLLM, notebooks, MLflow and others.

On the platform side, technologies: GoLang, Java, Spring Boot, REST APIs, Hibernate, SQL (PostgreSQL and MySQL) and NOSQL (Redis, MongoDB). 

We deploy everything to cloud-native Docker / Kubernetes environments, making use of GitHub + Actions, ArgoCD, Prometheus, and other modern cloud technologies.

You will work together with a creative and innovative group of people that love experimenting and learning new things. We are an international team that breaks barriers and solves real customer and business problems.

Main responsibilities:

Would you like to join the AI Technology team at IONOS (1&1 Internet), Europe’s leading cloud and web hosting provider? We are building a platform that provides AI solutions to customers worldwide, from GenAI / LLM inference, to model training, vector databases and much more.

We are looking for a Go Developer with Python knowledge to develop our AI Cloud platform, which provides GenAI and Machine Learning Services to customers in IONOS Cloud.

In this role, you will:

• Develop platform components, services and APIs, that integrate AI / ML services into our cloud products stack;
• Drive cloud-native implementation as part of a cross-functional team responsible for building our AI / ML platform that will provide AI-based products to our cloud customers, as well as internal clients and IONOS Group brands;
• Take part in all phases of development, maintenance and housekeeping of the platform;
• Work closely with Product Owners, Architects to define the best technical solutions that match our product vision;
• Collaborate with an international organization of software developers and AI enthusiasts.

We appreciate:

• Strong programming language in GO / Python, preferably more than one, and ecosystem knowledge with a 4+ years experience, or 7+ years for Senior level;
• Experience with cloud-native environments such as Docker, Kubernetes;
• Very good command of software design patterns and architectural concepts;
• Experience with building RESTful services;
• Ability to take on technical concepts and deliver solution for project initiatives;
• Microservice oriented architecture, performance and scalability concerns;
• Very good OOP and OOD experience;
• Experience with build tools and versioning systems, such as Git/GitHub/Gitlab, Actions, Jenkins, ArgoCD or similar;
• Good written and verbal English skills. 

Would be a plus:

• Product-oriented development mindset and a responsible ownership attitude towards software components;
• Previous experience integration AI / ML related solutions;
• Strong understanding of systems resilience, concurrency, and scalability concerns;
• Full-stack development skills are appreciated;
• Knowledge of Machine Learning technologies, working with data and ML models;
• Openness to take new approaches, learn new concepts and technologies;
• An open collaboration approach and transparent communication.

What we offer:

• Access to local/international trainings, development and growth opportunities, including access to e-learning platforms, covering both technical and soft skills areas;
• Modern technologies, product responsibility;
• Flexible work schedule;
• Hybrid work option;
• Medical services package from one of two private providers;
• 25 vacation days per year;
• Substitute days off for public holidays that occur on the weekend;
• Meal tickets;
• Internal referral program;
• Employee anniversary program;
• Team events, networking events organized to promote a passionate, creative and diverse culture;
• Summerfest and Winterfest parties;
• Of course, coffee, soft drinks and fresh fruits are on us in the office.

NTC OVERVIEW:  We are seeking a Data Scientist to join our team. Working at NT Concepts means that you are part of an innovative, agile company dedicated to solving the most critical challenges in National Security. We’re looking for the best and the brightest to join us in supporting this mission. If meaningful work, initiative, creativity, and continuous self-improvement are important to your career, join our growing team and discover What's Next for you. 

Mission Focus:  As a Data Scientist, you will have the unique opportunity to solve hard problems and help turn complex concepts into reality to advance and enhance systems supporting the defense of our nation. You will be part of a solutions-oriented, Agile/Scrum team designing and developing custom applications and components to support innovative data science capabilities. 

Our delivery teams are driven to explore new ideas and technology, and care deeply about collaboration, feedback, and iteration. We follow SAFe practices, embrace the Ops ethos (DataOps/DevSecOps/MLOps) to “automate-first”, use modern tech stacks, and constantly challenge each other to grow and improve. 

If cutting edge development projects resonate with you, and you care deeply about joining a mission-driven company with a strong growth direction and diverse culture, we'd love to learn more about you. Check out the details below, and let’s connect. 

Clearance: Active TS/SCI Poly clearance.  

Location/Flexibility: Chantilly, VA - 100% Onsite

Position Description:

• Perform research and development on advanced artificial intelligence and machine learning techniques for customers. 

• Communicate results of AI/ML research to non-technical audiences, translating complex findings into actionable insights. 

• Write efficient, distributed, and parallelized Python code to support AI/ML initiatives. 

• Organize and manage tasks using agile methodologies and tools such as JIRA and Confluence. 

• Liaison with mission partners to represent customer workflows and establish interorganizational relationships. 

• Assess, transform, organize, and optimize data for use by machine learning algorithms. 

• Generate representative data sets for systems development and data science initiatives. 

• Build data pipelines that enable data scientists, engineers, and other stakeholders. 

• Implement source code and code provided by the data science team. 

• Utilize analytical, statistical, and programming skills to collect, analyze, and interpret large data sets. 

• Develop data-driven solutions to difficult mission challenges. 

• Develop scripts and software programs to address requirements using programming languages, tools, and computational methods. 

• Develop and/or consult on advanced methodological approaches, statistical and algorithmic analysis, and/or tailored software application support. 

• Create quantitative and qualitative data analytics and models to represent human behavior. 

• Identify patterns in data and translate findings into actionable intelligence. 

• Cooperate with software professionals in integrating analytical logic into a general software framework. 

• Train and fine-tune foundation models to address real intelligence questions and advance the Intelligence Community. 
• Write compelling documentation and reports for decision makers. 

 Basic Qualifications:  

• Bachelor's degree in a technical field (Computer Science, Mathematics, Statistics, or related discipline). 

• 4+ years of Data Science experience, including designing and implementing data curation techniques, especially for imagery data. 

• Proficiency in Python and/or R, with experience using relevant programming languages and technologies. 

• Familiarity with an array of data science tools and languages including Python, R, SQL, and others as needed. 

• Experience with Machine Learning, Computer Vision, and Object Detection. 

• Experience building and maintaining ETL pipelines, including Kubeflow pipelines. 

• Hands-on experience with imagery data, overhead imagery (optical or Synthetic Aperture Radar (SAR)), and synthetic data. 

• Strong understanding of large-scale distributed processing and parallel computing. 

• Familiarity with machine and deep learning libraries such as Scikit-learn, TensorFlow, and PyTorch. 

• Experience organizing and managing tasks in an agile environment (JIRA/Confluence). 

• Ability to build and maintain strong relationships with mission partners and stakeholders. 

• Proficient with Git version control systems and comfortable working in Linux OS environments. 

• Prior experience with PyTorch, Keras, and overhead imagery would be beneficial but is not required. 

Physical Requirements:

• Prolonged periods of sitting at a desk and working on a computer
• Must be able to lift 10-15 pounds at times.

#JT

As a Principal Machine Learning Engineer at CMT, you will develop algorithms that represent physical phenomena associated with both vehicle and human movements when measured by cell phone sensors and IoT devices. You will solve challenging real-world problems and assist in the development of innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets. Using knowledge of statistics, machine learning / deep learning, signal processing, physics, programming and data modeling, the Principal Machine Learning Engineer consults on Data Science projects, and works independently on developing new solutions to achieve CMT’s objectives, and making valuable discoveries which lead to company-wide prototype development and product improvements. 

CMT is looking for a Principal Machine Learning Engineer to help us change the world. CMT has helped protect over 65 million drivers and prevent over 126,000 crashes worldwide. We build AI to solve some of the most difficult challenges in mobility — understanding and reducing risk, detecting crashes, and getting people life-saving help. The problems are hard. The impact is real. No matter your role, your work will matter at CMT.

Responsibilities: 

• Use independent judgment and discretion to spearhead the creation of innovative and cutting-edge algorithmic solutions, utilizing unconventional approaches to address complex challenges. These solutions should have a far-reaching impact on the company, and involve the development of new features and products for customers using diverse data sources 
• Lead and mentor a team of talented junior machine learning engineers, guiding them through every phase of solution development, from meticulous data pre-processing and advanced modeling, to rigorous testing, seamless roll-out, and continuous performance monitoring in live production environments
• Demonstrate exceptional communication skills to effectively convey and present complex data science concepts to stakeholders across the organization. Foster a collaborative environment by actively engaging with diverse teams and promoting cross-functional cooperation 
• Stay at the forefront of research and emerging trends in the field of data science. Evaluate and validate the potential impact of incorporating new ideas into the platform, products, and customer experiences, ensuring continuous enhancement and innovation 
• Complete any additional tasks as they arise 

Qualifications: 

• Bachelor’s degree or equivalent years of experience and/or certification in Data Science, Computer Science, Electrical Engineering, Physics or Mathematics 
• 7+ years of experience in the Data Science field 
• 3+ years of experience developing commercial software with strong algorithmic, AI/machine learning, or signal processing components 
• Deep understanding of data science principles, algorithms and practices, such as deep learning / machine learning, statistics and probability, signal processing, and sensor physics
• Must possess a thorough knowledge and practice of software development process in large scale, and proven coding skills using scripting languages e.g. Python, Pandas, NumPy, scikit-learn, SQL
• Advanced knowledge of Big Data infrastructure, computation and storage as well as scalable AI/ML platforms & tools, e.g. Spark, Ray, TensorFlow, Keras, Torch, Caffe, etc. 
• Strong visualization and data literacy skills, with demonstrated ability to summarize mathematical representations into simple data visualizations and statistical results 
• Strong customer-focus and presentation skills with the ability to obtain requirements and influence outcomes

Nice to Haves: 

• Master’s or Ph.D. preferred

Compensation and Benefits:

• Fair and competitive salary based on skills and experience, and annual performance bonus
• Equity may be awarded in the form of Restricted Stock Units (RSUs)
• Medical, Dental, Vision and Life Insurance, matching 401k, short-term & long-term disability and parental leave
• Unlimited Paid Time Off including vacation, sick days & public holidays
• Flexible scheduling and work from home policy depending on role and responsibilities

Base Salary Range

• The base salary range for this position is: $177,000 to $221,300.  This range is specifically for Cambridge, MA

Additional Perks:

• Work on a mission with real impact: crashes prevented, injuries avoided, lives protected around the world
• Join an industry leader — 65 million drivers protected, powering 140+ programs across 25 countries
• Be part of the team inventing the future of mobility and road safety
• Move fast, own outcomes, do work that matters
• High ownership, small teams, and direct access to leadership — no layers between your work and its impact
• Unlimited PTO, flexible scheduling, competitive salary, annual performance bonus, RSUs, and full benefits including medical, dental, vision, and 401k match
• Summer Fridays
• Join one of our employee resource groups: Black, AAPI, LGBTQIA+, Women, Book Club, and Health & Wellness
• Comprehensive wellness, education, and employee assistance programs

Commitment to Diversity and Inclusion:

At CMT, we believe the best ideas come from a mix of backgrounds and perspectives. 

We are an equal-opportunity employer committed to creating a workplace and culture where everyone feels valued, respected, and empowered to bring their unique talents and perspectives. Diversity is essential to our success, and we actively seek candidates from all backgrounds to join our growing team. 

We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability state. CMT is headquartered in Cambridge, MA. To learn more, visit www.cmtelematics.com and follow us on X @cmtelematics.

About Cambridge Mobile Telematics:

Cambridge Mobile Telematics (CMT) is the world’s largest telematics and AI company for safer mobility. Its mission is to make the world’s roads and drivers safer. The company’s AI-driven platform, DriveWell Fusion®, proactively identifies and reduces driving risk, leading to fewer crashes and injuries. To date, CMT’s technology has helped prevent over 126,000 crashes worldwide. CMT enables partners to measure risk, detect crashes, provide life-saving assistance, and streamline claims. Headquartered in Cambridge, MA, CMT operates globally with offices in Budapest, Hungary; Chennai, India; Seattle, Washington; Tokyo, Japan; and Zagreb, Croatia. Learn more at www.cmt.ai.

CMT is building DriveWell Atlas, a family of foundation models trained on large-scale, multi-modal telematics signals (e.g., inertial sensors, GPS-derived signals, device/context features) to power safer driving outcomes across risk, safety, crash and claims workflows. 

As an IC2 Foundation Models contributor, you will work closely with senior scientists and engineers to prototype, train, evaluate, and deploy time-series foundation models—while also helping optimize the underlying training/inference systems for scale and efficiency. This role is hands-on, highly technical, and well-suited for someone with strong software fundamentals and growing applied ML experience. CMT has helped protect over 65 million drivers and prevent over 126,000 crashes worldwide. We build AI to solve some of the most difficult challenges in mobility — understanding and reducing risk, detecting crashes, and getting people life-saving help. The problems are hard. The impact is real. No matter your role, your work will matter at CMT.

Responsibilities: 

• Use independent judgment and discretion to develop ML / DL models which pattern driving behaviors and vehicle kinematics in data collected via smartphone sensors 
• Assist with projects and solutions through the full development stages, from data pre-processing, modeling, testing, through roll-out with minimum management oversight 
• Write code for debugging complex issues and creating new solutions that will run as part of production systems 
• Support customers’ requests regarding the production ML models and derive deep insights from data
• Use independent judgment and discretion to communicate and present data science work within the data science team as well as to stakeholders across the org and to collaborate across different teams 
• Complete any additional tasks as they arise 

Qualifications: 

• Bachelor’s degree or equivalent years of experience and/or certification in Data Science, Computer Science, Statistics, Mathematics or Engineering 
• 2+ years of professional experience in the Data Science field 
• A good understanding of data science principles, algorithms and practices, such as machine learning, deep learning, statistics and probability 
• Knowledge of software development process, and proven coding skills using scripting languages e.g. Python, Pandas, NumPy, scikit-learn and SQL 
• Ability to write and navigate code, request data from data sources and code from scratch
• Experience with deep learning frameworks (TensorFlow, Keras, Torch, Caffe, etc.) and knowledge of Big Data infrastructure (Hadoop, Spark, etc.) will be a plus 
• A great team player and quick learner

Nice to haves:

• Experience with one or more of the following:
• • Time-series / sensor modeling (inertial signals, GPS-derived features, mobile/IoT data)
  • Distributed systems or big-data processing (streaming/batch pipelines; e.g., Kafka/Spark/Ray-style ecosystems)
  • GPU programming / performance optimization (CUDA, kernel-level efficiency, profiling/benchmarking, mixed precision training, and memory/performance tuning)
  • Model compression techniques (post-training quantization, pruning)
  • Demonstrated ability to translate ideas into working prototypes (course projects, research, prior roles).

Compensation and Benefits:

• Fair and competitive salary based on skills and experience, and annual performance bonus
• Equity may be awarded in the form of Restricted Stock Units (RSUs)
• Medical, Dental, Vision and Life Insurance, matching 401k, short-term & long-term disability and parental leave
• Unlimited Paid Time Off including vacation, sick days & public holidays
• Flexible scheduling and work from home policy depending on role and responsibilities

Base Salary Range

• The base salary range for this position is: $123,000 to $153,700. This range is specifically for Cambridge, MA

Additional Perks:

• Work on a mission with real impact: crashes prevented, injuries avoided, lives protected around the world
• Join an industry leader — 65 million drivers protected, powering 140+ programs across 25 countries
• Be part of the team inventing the future of mobility and road safety
• Move fast, own outcomes, do work that matters
• High ownership, small teams, and direct access to leadership — no layers between your work and its impact
• Unlimited PTO, flexible scheduling, competitive salary, annual performance bonus, RSUs, and full benefits including medical, dental, vision, and 401k match
• Summer Fridays
• Join one of our employee resource groups: Black, AAPI, LGBTQIA+, Women, Book Club, and Health & Wellness
• Comprehensive wellness, education, and employee assistance programs

Commitment to Diversity and Inclusion:

At CMT, we believe the best ideas come from a mix of backgrounds and perspectives. 

We are an equal-opportunity employer committed to creating a workplace and culture where everyone feels valued, respected, and empowered to bring their unique talents and perspectives. Diversity is essential to our success, and we actively seek candidates from all backgrounds to join our growing team. 

We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability state. CMT is headquartered in Cambridge, MA. To learn more, visit www.cmtelematics.com and follow us on X @cmtelematics.

About Cambridge Mobile Telematics:

Cambridge Mobile Telematics (CMT) is the world’s largest telematics and AI company for safer mobility. Its mission is to make the world’s roads and drivers safer. The company’s AI-driven platform, DriveWell Fusion®, proactively identifies and reduces driving risk, leading to fewer crashes and injuries. To date, CMT’s technology has helped prevent over 126,000 crashes worldwide. CMT enables partners to measure risk, detect crashes, provide life-saving assistance, and streamline claims. Headquartered in Cambridge, MA, CMT operates globally with offices in Budapest, Hungary; Chennai, India; Seattle, Washington; Tokyo, Japan; and Zagreb, Croatia. Learn more at www.cmt.ai.

Note: This isn’t an active role right now, but we’re building a community of great talent for future opportunities at Caylent. If your background aligns with what we’re looking for, our team may reach out to learn more about you and explore potential future fits.

The Mission

At Caylent, a Senior Machine Learning Engineer works as an integral part of a cross-functional delivery team to design and document machine learning solutions on the AWS cloud for our customers.  We are looking for someone that has a strong understanding of the various model types and tools, and can help our customers connect their business goals with the details of feature design, model training and inference.  You will develop solutions designed by an architect.

You will participate in daily standup meetings with your team and bi-weekly agile ceremonies with the customer.  Your manager will have a weekly 1:1 with you to help guide you in your career and make the most of your time at Caylent.

Your Assignments

• Work with a team to deliver machine learning solutions on AWS for customers
• Participate in and contribute to daily standup meetings
• Develop and implement ML models, MLOps, and analytics
• Big data processing and preparation of training data for models

Your Qualifications

• Strong experience in building ML models for real world applications
• Strong experience in at least one of these:
• AWS ML Services/SageMaker
• ML libraries like Keras, Tensorflow, PyTorch, Scikit-learn
• MLOps tools such as MLflow, Kubeflow, Airflow
• Advanced analytics using time series forecasting and/or inferential statistics
• Strong experience in one or more of these data processing solutions:
• Big data processing platforms like Spark, Hadoop, or streaming platforms
• Data processing and cleansing using Python/Pandas, PySpark, Scala, SQL
• Strong understanding of feature definition, model meta-data, hyperparameter tuning, stochastic gradient descent, deep learning layer types and activation functions
• Experience in visualization using SageMaker, ggplot, matplotlib, or seaborn
• Experience with an IaC tool such as CloudFormation, Amazon CDK or Terraform
• Excellent written and verbal communication skills

Benefits 

• Pay in USD
• 100% remote work
• Generous holidays and flexible PTO
• Competitive phantom equity
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture

This role may require up to 25% travel, depending on business needs. 

Note: This isn’t an active role right now, but we’re building a community of great talent for future opportunities at Caylent. If your background aligns with what we’re looking for, our team may reach out to learn more about you and explore potential future fits.

The Mission

At Caylent, a Senior Machine Learning Engineer works as an integral part of a cross-functional delivery team to design and document machine learning solutions on the AWS cloud for our customers.  We are looking for someone that has a strong understanding of the various model types and tools, and can help our customers connect their business goals with the details of feature design, model training and inference.  You will develop solutions designed by an architect.

You will participate in daily standup meetings with your team and bi-weekly agile ceremonies with the customer.  Your manager will have a weekly 1:1 with you to help guide you in your career and make the most of your time at Caylent.

Your Assignments

• Work with a team to deliver machine learning solutions on AWS for customers
• Participate in and contribute to daily standup meetings
• Develop and implement ML models, MLOps, and analytics
• Big data processing and preparation of training data for models

Your Qualifications

• Strong experience in building ML models for real world applications
• Strong experience in at least one of these:
• AWS ML Services/SageMaker
• ML libraries like Keras, Tensorflow, PyTorch, Scikit-learn
• MLOps tools such as MLflow, Kubeflow, Airflow
• Advanced analytics using time series forecasting and/or inferential statistics
• Strong experience in one or more of these data processing solutions:
• Big data processing platforms like Spark, Hadoop, or streaming platforms
• Data processing and cleansing using Python/Pandas, PySpark, Scala, SQL
• Strong understanding of feature definition, model meta-data, hyperparameter tuning, stochastic gradient descent, deep learning layer types and activation functions
• Experience in visualization using SageMaker, ggplot, matplotlib, or seaborn
• Experience with an IaC tool such as CloudFormation, Amazon CDK or Terraform
• Excellent written and verbal communication skills

Benefits 

• 100% remote work
• Medical Insurance for you and eligible dependents
• Generous holidays and flexible PTO
• Competitive phantom equity
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture

This role may require up to 25% travel, depending on business needs.

Note: This isn’t an active role right now, but we’re building a community of great talent for future opportunities at Caylent. If your background aligns with what we’re looking for, our team may reach out to learn more about you and explore potential future fits.

The Mission

At Caylent, a Senior Machine Learning Engineer works as an integral part of a cross-functional delivery team to design and document machine learning solutions on the AWS cloud for our customers.  We are looking for someone that has a strong understanding of the various model types and tools, and can help our customers connect their business goals with the details of feature design, model training and inference.  You will develop solutions designed by an architect.

You will participate in daily standup meetings with your team and bi-weekly agile ceremonies with the customer.  Your manager will have a weekly 1:1 with you to help guide you in your career and make the most of your time at Caylent.

Your Assignments

• Work with a team to deliver machine learning solutions on AWS for customers
• Participate in and contribute to daily standup meetings
• Develop and implement ML models, MLOps, and analytics
• Big data processing and preparation of training data for models

Your Qualifications

• Strong experience in building ML models for real world applications
• Strong experience in at least one of these:
• AWS ML Services/SageMaker
• ML libraries like Keras, Tensorflow, PyTorch, Scikit-learn
• MLOps tools such as MLflow, Kubeflow, Airflow
• Advanced analytics using time series forecasting and/or inferential statistics
• Strong experience in one or more of these data processing solutions:
• Big data processing platforms like Spark, Hadoop, or streaming platforms
• Data processing and cleansing using Python/Pandas, PySpark, Scala, SQL
• Strong understanding of feature definition, model meta-data, hyperparameter tuning, stochastic gradient descent, deep learning layer types and activation functions
• Experience in visualization using SageMaker, ggplot, matplotlib, or seaborn
• Experience with an IaC tool such as CloudFormation, Amazon CDK or Terraform
• Excellent written and verbal communication skills

Benefits 

• 100% remote work
• Generous holidays and flexible PTO
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture

This role may require up to 25% travel, depending on business needs.

Overview

We are looking for interns to join Instacart’s Economics team. The ideal candidate for this role will bring a combination of experience in both economics and machine learning. We are in particular looking for current or recently graduated PhD students in economics or related fields like marketing, finance, or operations research. Candidates should bring some relevant research experience, typically in computationally intensive empirical topics, as well as some exposure to machine learning coursework and applications.

The Economics team at Instacart works on a range of interesting and challenging problems at the intersection of machine learning and economics, from aligning the incentives in our multi-sided marketplace to analyzing the impact of behavioral nudges on our customers’ and shoppers’ decisions. Some of the core areas of focus for our team include online advertising, uplift and long term value modeling, logistics, marketplace optimization (consumers, shoppers, retailers), inventory intelligence, and general causal inference. You can find more information in our blog post that introduces the team and the type of work we do.

About the Job

• You will help design and build end-to-end machine learning solutions.
• You will be working in small and cross-functional product teams, with great opportunities for growth and ownership of projects.
• You will be an active member of an internal community, including economists, data scientists, operations research scientists and machine learning engineers, sharing learnings, best practices and research across many domains.
• You will develop high impact solutions to support Instacart's ambitious growth plans.
• You will work closely with engineers, product managers, other teams, and both internal and external stakeholders, owning a large part of the process from problem understanding to recommending a solution and testing it in controlled experiments.
• You will have the freedom to suggest and drive organization-wide initiatives.

About You

Minimum Qualifications

• Current or recently graduated PhD student in economics or a related field with focus on data-intense problems.
• A blend of economic theory, applied econometrics, and business acumen that let you jump into a fast-paced environment and contribute from day one.
• Expertise in causal inference with observational and experimental data.
• Expertise in Python or R and fluency in data manipulation (SQL, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools.
• Self-motivation and a strong sense of ownership