Who we are

About Stripe

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

About the team

The Stream Compute team at Stripe builds and operates the infrastructure, tooling, and systems behind our Flink-powered stream processing systems. We're at the heart of several core asynchronous workflows, operating at significant scale and handling vast amounts of sensitive financial data. Our work powers intricate processes involving various critical financial operations and real-time analytics. We run globally distributed systems with high reliability and performance to meet Stripe's scaling, availability, and product needs, and we continually reduce operational toil by investing in automation and self-service tooling for upgrades, maintenance, and day-to-day operations. The team is distributed between Seattle, Toronto and remote locations.

What makes our team truly exciting is our commitment to our users: we ensure no event is dropped, state integrity is preserved, and support exactly-once processing as a first-class feature. Working at the intersection of real-time data processing and fintech innovation, we continuously push the boundaries of what's possible. Our focus on innovation, user experience, reliability, and compliance drives increased ROI and operational excellence, making us a crucial part of Stripe's success.

What you'll do

You'll help define and deliver the next generation of Stripe's Flink-first stream compute infrastructure—driving innovation to meet extremely high availability targets at global scale. Partnering with infrastructure engineers, adjacent platform teams, and the product orgs that depend on Flink every day, you'll set a long-term technical direction that scales with Stripe's growth while enabling reliable, efficient operations for years to come. You'll work on the hardest problems in operating Flink in production—state management, exactly-once processing, performance isolation, and automated recovery—so teams across Stripe can confidently build stateful stream processing applications on top of it.

Responsibilities

• Design, build, and operate stream compute infrastructure with Apache Flink at the center, alongside technologies like Kafka, Temporal, and AWS services
• Partner with product and platform teams across Stripe to understand requirements, unblock Flink adoption, and improve how stream processing infrastructure is used end-to-end
• Define and implement operational best practices (e.g., shuffle sharding, cellular architecture, load shedding, automated state recovery) to improve resilience and reliability at scale
• Drive fleet-level automation and standardization ("pets" to "cattle") through self-service workflows, safer rollouts, and self-healing systems that reduce manual operations
• Lead initiatives that raise the bar on Flink availability and state durability (e.g., multi-region strategies, disaster recovery readiness, operational readiness reviews, incident learning)
• Evaluate and productionize Flink ecosystem capabilities (e.g., SQL, connectors, state backends) to improve developer experience and scalability without compromising reliability
• Work closely with the open source community to identify opportunities for adopting new open source features as well as contribute back to OSS

Who you are

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

Minimum requirements

• This is a Staff-level role - that typically means 10+ years of experience building, operating, and evolving large-scale production systems
• Experience as a technical lead for team(s) working on distributed systems, including scaling them in fast-moving environments
• Hands-on experience with big data technologies such as Flink, Spark, Kafka, Pulsar, or Pinot
• Experience developing, maintaining and debugging distributed systems built with open source tools
• Experience building and scaling infrastructure as a product
• Strong software engineering skills and a passion for Big Data Distributed Systems
• Ability to write high quality code (in programming languages like Go, Java, Scala, etc)
• Comfortable operating with high autonomy and ownership
• Growth mindset and a willingness to learn quickly, explore ambiguous problem spaces, and dive deep when needed
• Strong written and verbal communication skills, including the ability to produce clear technical documentation

Preferred qualifications

• Experience operating streaming infrastructure as a platform (e.g., Flink clusters, Kafka, Pulsar) for internal customers at scale
• Deep hands-on experience authoring, optimizing, and operating real-time processing frameworks such as Flink, Spark Streaming, Storm, or Kafka Streams in production
• Experience building or operating control planes for managing large-scale infrastructure
• Open source contributions to data processing or big data systems (Hadoop, Spark, Celeborn, Flink, etc)

As a Sr. Solutions Architect at Databricks within the Field Engineering org, you will partner with our customers to design scalable data architectures using Databricks technology and services. You have technical depth and business knowledge, and can drive complex technology discussions that express the value of the Databricks platform throughout the sales lifecycle. In partnership with our Account Executives, you will engage with our customers' technical leads, including architects, engineers, and operations teams, with the goal of establishing yourself as a trusted advisor to achieve tangible outcomes. You will work with teams across Databricks and our executive leadership to represent your customers' needs, build valuable customer engagements, and report to the Field Engineering Manager.

The impact you will have:

• You will work with Sales and other essential partners to develop account strategies for your assigned accounts to grow their usage of the platform.
• Establish the Databricks Lakehouse architecture as the standard data architecture for customers through excellent technical account planning.
• You will build and present reference architectures and demo applications for prospects to help them understand how Databricks can be used to achieve their goals to land new users and use cases.
• Capture the technical win by consulting on big data architectures, data engineering pipelines, and data science/machine learning projects; prove out the Databricks technology for strategic customer projects; and validate integrations with cloud services and other 3rd party applications.
• Become an expert in and promote Databricks-inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars.

What we look for:

• 8+ years in a customer-facing pre-sales or consulting role with expertise in at least one of the following technologies:
• Big data engineering (Ex: Spark, Hadoop, Kafka)
• Data Warehousing & ETL (Ex: SQL, OLTP/OLAP/DSS)
• Data Science and Machine Learning (Ex: pandas, scikit-learn, HPO)
• Data Applications (Ex: Logs Analysis, Threat Detection, Real-time Systems Monitoring, Risk Analysis and more)
• Experience translating a customer's business needs to technology solutions, including establishing buy-in with essential customer stakeholders at all levels of the business.
• Experienced at designing, architecting, and presenting data systems for customers and managing the delivery of production solutions of those data architectures.
• Fluent in SQL and database technology.
• Debug and development experience in at least one of the following languages: Python, Scala, Java, or R.
• [Desired] Built solutions with public cloud providers such as AWS, Azure, or GCP
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Travel to customers in your region up to 30% of the time.

Job Duties: Design, develop, and apply DS solutions to inform improvements in advertiser experience as well as Reddit ad platform and marketplace performance. Analyse large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform. Collaborate with product managers and engineers to define product requirements and translate them into data science solutions. Develop Machine Learning models and Data Science methods to improve anomaly detection, prediction and pattern recognition. Communicate findings and recommendations to stakeholders across the organization. Telecommuting permitted. 

Minimum Requirements: Master’s degree (or its foreign equivalent) in Computer Science, Information Management, Statistics, Mathematics, or closely related quantitative field and two (2) years of experience in data science, machine learning, or a related field.

Special Skill Requirements: (1) Statistical modelling (2) Machine learning algorithms (3) Causal inference (4) Experimentation design (5) Large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive (6) Python or R (7) Machine learning libraries such as scikit-learn, TensorFlow, or PyTorch (8) SQL and relational databases Any suitable combination of education, training and experience is acceptable. Experience can be gained through coursework, scholastic achievement, or work experience.

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

Submit a resume with references using the apply button on this posting or by email at: applicationsreview@reddit.com at Req.# 1016.238.2.

Pay Transparency:

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.

To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. 

The base pay range for this position is: $164,200.00 - $229,900.00 USD

#LI-DNI

About the Role

You are a Data Engineer, who is passionate about writing beautiful code and building great products. You have an intuitive sense of the right tools and frameworks to use to solve a given problem. You are not afraid to traverse the entire spectrum of the development process from writing code and testing to deploying and managing your systems in production. You are smart but know that there is no substitute for hard work. You have good communication skills, a ‘can do’ entrepreneurial attitude, and a team-oriented mindset.

Key Responsibilities

• Design and build data transformations efficiently and reliably for different purposes (e.g. reporting, growth analysis, multi-dimensional analysis)

• Design and implement reliable, scalable, robust and extensible big data systems that support core products and business

• Establish strong engineering design standards and best practices for both technical and non-technical stakeholders

Required Qualifications and Must-Have Skills

• BS/MS degree in Computer Science or related technical field or equivalent practical experience

• Experience in the Big Data technologies (Hadoop, M/R, Hive, Spark, Flink, Metastore, Presto, Kafka etc.)

• Experience with performing data analysis, data ingestion and data integration

• Experience with ETL (Extraction, Transformation & Loading) and architecting data systems

• Experience with schema design, data modeling and SQL queries

• Hands-on experience using modern AI coding assistants (e.g., Claude Code, Windsurf, or equivalent) to design, implement, and optimize data pipelines and large-scale data processing systems

• Passionate and self-motivated about technologies in the Big Data area

Nice to Have Skills

• Experience with Django framework

• Exposure to AWS

Interpersonal Attributes

• You can work independently as well as part of a team

• You take ownership of projects and drive them to conclusion

• You’re a good communicator and are capable of not just doing the work, but teaching others and explaining the “why” behind complicated technical decisions

• You can present your architecture and designs to cross teams

• You aren’t afraid to roll up your sleeves: This role will evolve over time, and we’ll want you to evolve with it!

Base Salary Range: $179,400.00 - $263,120.00. The base salary range represents the anticipated low and high end of the base salary range for this position. Actual salaries may vary and may be above or below the range based on various factors, including but not limited to work location and experience. The base salary is one component of 6sense’s total compensation package for this position. Other compensation may include a bonus program or commission plan, and stock options if approved by 6sense’s board. In addition, 6sense provides a variety of benefits, including generous health insurance coverage, life, and disability insurance, a 401K employer matching program, paid holidays, self-care days, and paid time off (PTO). #Li-remote

Notice of Collection and Use of Personal Information for California Residents: California Recruitment Privacy Notice and Policy

SoFi is seeking an experienced and motivated Senior Staff Data Engineer to be the technical leader of our Data Engineering group within the SoFi Data Platform(SDP) division. The mission of the SDP division is to activate data throughout SoFi, enabling the creation of personalized and delightful experiences for our members. 

The Role:

In this role, you will have the opportunity to directly impact, influence and lead the direction and architecture of our next gen AI powered SoFi Data Platform(SDP), and elevate data reliability through AI enabled workflows, tooling and practices. You will get the chance to lead, define, and take on complex and interesting problems as part of a fast-paced, highly collaborative organization. The ideal candidate will be a mentor, technical leader and a team player who is hands-on and comfortable driving solutions from initial architecture to implementation and adoption with a strong sense of ownership and drive for delivery. 

What You’ll Do: 

• Technical Leadership & Strategy: As a technical leader, you will be at the heart of SoFi’s data platform providing primary technical authority and strategic guidance to the data engineering group. 
• Architectural Excellence: Lead the architecture and delivery of large-scale, high-performance data pipelines and processing frameworks. Design scalable data models that support analytics, AI/ML and real-time data needs.
• Platform Innovation: Drive the adoption of cloud-native technologies, automation frameworks and reusable components that improve development velocity and system reliability across SDP.
• System Optimization: Drive org-wide initiatives to improve data reliability, cost-efficiency, and latency. Design solutions that scale horizontally and vertically to handle ever-growing datasets.
• Cross-Functional Collaboration: Partner with business stakeholders, product and engineering leads to align the data roadmap with SoFi’s business objectives. 
• Governance & Security: Lead the implementation of sophisticated data privacy, security, and compliance frameworks. Enforce data governance policies and practices to maintain data integrity in a highly regulated environment.
• Mentorship: Provide deep technical coaching and mentorship to Staff and Senior data engineers, fostering a culture of continuous learning, rigorous testing, and engineering excellence.
• Workforce Development: Contribute to hiring and training efforts to build a skilled and motivated data engineering workforce. Lead the interview process for senior-level talent and design onboarding programs that accelerate engineering productivity.
• On-Call Support: Be part of an on-call support rotation to support the critical production systems.

What You'll Need: 

• Education: A bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
• Experience: Over 12 years of experience in data engineering and analytics, with at least 4 years in a staff-level or higher capacity. A proven track record of successfully leading enterprise-wide data modernization efforts.
• Tech Stack Mastery: Mastery of the modern data stack: Snowflake / Python / SQL / GitLab / AWS / Airflow/ AI tools like Claude code/Cursor. Understanding and implementation experience of AI agents is a plus.
• Cloud Architecture: Expert-level proficiency in relational and cloud database platforms (Snowflake, Redshift, or GCP) and distributed processing frameworks (Hadoop, Spark, or Kafka).
• Strategic Thinking: Thorough knowledge and passion for data modeling (Kimball/Data Vault), database design, and data architecture principles. Ability to simplify complex, ambiguous issues into actionable technical plans.
• Communication: Exceptional ability to communicate complex technical concepts and trade-offs to non-technical stakeholders and senior management.

Domain Knowledge: Deep experience in a highly regulated and governed sector; experience in the Fintech industry is highly advantageous.

We are looking for a Sr. Staff Machine Learning Engineer to be the Technical Lead for the Content Quality who will build the overall technical strategy, unified technical architecture and define a roadmap for industry leading methodology. We are seeking strong hands on machine learning background including content modeling, signal lifecycle, and platforms used to enforce signal use with downstream use cases.

You’ll be working with other leads to set and execute a long-term strategy for the team, aligning the strategy with other clients where it makes sense and communicating to leadership our current status and path to having world-class capabilities. You'll also foster a healthy community where all Content Quality engineers can learn best practices, collaborate effectively and understand our technical direction. 

What you’ll do:

• Architect and develop a roadmap and processes for building and delivering signals capturing quality and trust aspects of content at Pinterest.
• Drive safety of GenAI and Conversational use cases including safety alignment and VLMs.
• Work with downstream teams to align on use cases, evaluate signal impact, and drive adoption of signals in models, ranking systems, and decision-making workflows.
• Partner closely with ML engineers to translate ideas into production-ready signals, from problem formulation and feature design to validation and deployment.

What we’re looking for:

• Experience driving technical strategy at an organizational level.
• Expertise in content modeling at consumer internet scale.
• Using GenAI for scaling ML development.
• Strong ability to work cross-functionally and with partner engineering teams.
• Experience working with multiple stakeholders.
• Strong measurement and scalability experience.
• Strong ML knowledge and expertise.
• Hands-on experience with big data technologies (e.g., Hadoop / Spark / Kafka / Flink) is a plus.
• Machine Learning at scale deployment experience (note this is different from having ML theoretical knowledge, which is a nice to have).
• Thought Leadership: Publication and/or conference speaking experience is a plus.
• Nice to have: 
  • Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring.
  • Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration.

In-Office Requirement Statement:

• We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

#LI-HYBRID

#LI-AK7

With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.

Within the Monetization ML Engineering team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. In this role, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads.

What you’ll do:

• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
• Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
• Work in a high-impact environment with quick experimentation and product launches
• Keep up with industry trends in recommendation systems 
• Leverage LLMs to enhance content understanding

What we’re looking for:

• 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
• Degree in computer science, statistics, or related field; or equivalent experience
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
• Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems
• Nice to have:
  • M.S. or PhD in Machine Learning or related areas
  • Publications at top ML conferences
  • Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
  • Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
  • Expertise in scalable realtime systems that process stream data
  • Passion for applied ML and the Pinterest product
  • Background in computational advertising

Relocation Statement: 

•  This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

#LI-HYBRID

With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 3,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.

What you’ll do:

• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
• Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
• Work in a high-impact environment with quick experimentation and product launches
• Keeping up with industry trends in recommendation systems 

What we’re looking for:

• 4+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
• Degree in computer science, machine learning, statistics, or related field
• Nice to have:
  • Publications at top ML conferences
  • Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
  • Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
  • Expertise in scalable realtime systems that process stream data
  • Passion for applied ML and the Pinterest product
  • MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences, related field, or equivalent experience.

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

#LI-SA1

#LI-REMOTE

With more than 600 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.

Within the Monetization ML Engineering team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. In this role, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads.

What you’ll do:

• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
• Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
• Work in a high-impact environment with quick experimentation and product launches
• Keep up with industry trends in recommendation systems 
• Leverage LLMs to enhance content understanding

What we’re looking for:

• 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
• Degree in computer science, machine learning, statistics, or related field
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
• Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems
• Nice to have:
  
  • Publications at top ML conferences
  • Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
  • Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
  • Expertise in scalable realtime systems that process stream data
  • Passion for applied ML and the Pinterest product
  • Background in computational advertising

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

#LI-HYBRID

#LI-SM4

With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 3,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.

What you’ll do:

• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
• Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
• Work in a high-impact environment with quick experimentation and product launches
• Keeping up with industry trends in recommendation systems 

What we’re looking for:

• 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
• Degree in computer science, machine learning, statistics, or related field
• Nice to have:
  • M.S. or PhD in Machine Learning or related areas
  • Publications at top ML conferences
  • Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
  • Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
  • Expertise in scalable realtime systems that process stream data
  • Passion for applied ML and the Pinterest product

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

#LI-SA1

#LI-REMOTE

As a Hunter Solutions Architect on the Digital Natives team, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world.

Reporting to the Field Engineering Manager, you will collaborate with customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.

The impact you will have:

• You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
• Work directly with prospective, greenfield, customers on their 0 to 1 journey with Databricks 
• Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
• Collaborate with your fellow Solutions Architects, using your skills to support each other and our users
• Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.

What we look for:

• 5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
• Experience building distributed data systems at scale 
• Comfortable programming in, and debugging, Python and SQL
• Experience using agentic coding harnesses and demonstrable experience scaling your work leveraging them 
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Expertise in one of the following:
• Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
• Available to travel to customers in your region
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Nice to have: Databricks Certification

NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply.  We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.

While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. #LI-REMOTE

As a Solutions Architect on the Digital Natives team, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world.

Reporting to the Field Engineering Manager, you will collaborate with customer stakeholders, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide one of our largest AI native customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.

The impact you will have:

• You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
• Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
• Collaborate with your fellow Solutions Architects, using your skills to support each other and our users
• Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.

What we look for:

• 7+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
• Experience building distributed data systems
• Comfortable programming in, and debugging, Python and SQL
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Expertise in one of the following:
  • Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
  • Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
• Available to travel to customers in your region
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Nice to have: Databricks Certification

NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply.  We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.

Location: United States (remote)

What is Verse? 

Energy markets are more volatile than ever. Rapid electrification and the rise of AI are driving unprecedented demand for power, while energy costs continue to rise across the globe. For the world’s largest energy buyers, managing energy has never been more complex or more critical.

Verse helps these organizations manage complex power portfolios with confidence by unifying energy data, planning, forecasting, and operations in one tool. Our Energy Cost Intelligence platform, Aria, brings together energy, finance, and operations teams with real-time, finance-ready intelligence—replacing spreadsheets and consultants with precision across the entire energy lifecycle. Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster, smarter energy decisions that reduce risk and lower energy costs.

The Role

You will be a member of the technical staff designing, building, and maintaining the next generation of data platform tools, pipelines, and orchestration frameworks to support multiple teams and products across a diverse range of data at Verse. This role supports Core Engineering needs within the organization and builds on top of existing engineering foundations focused on data. As a technical leader with advanced data engineering expertise, teammates will look to you to vet proposals, solutions to internal and customer-facing problems, system designs, and drive the implementation of these solutions with highest standards of software-engineering best practices. You will be an integral part of scaling our data platform as the company grows.

Key Responsibilities

• Ensure data quality, contracts and integrity with best practices around access, governance, and federation throughout the data lifecycle
• Implement, maintain, and promote best practices and hygiene in our dataland code repository for others to follow and emulate
• Write shared libraries and reusable data tools across a variety of data flows, sources, and sinks
• Partnering closely with our Data Science and data-heavy internal teams to support various analytical and AI/ML workflows
• Foster a culture and mindset of well-designed systems, test-driven software, and proactive communication with a high degree of transparency, mutual respect, and consideration for teammates
• Participate in code reviews, maintain technical documentation, and adhere to best software development practices

What We're Looking For (Minimum Qualifications)

• Advanced software development skills in Python, Rust, Java, Scala, or similar data-oriented language ecosystems
• Deep understanding of databases, data {lake,ware}house architectures, and data pipeline solutions across heterogeneous data and workloads in cloud-native environments
• Proficiency in carefully handling large, complex data and processing them (streaming and batch) in both transactional and analytical settings
• Commitment to delivering high quality software on time or ahead of schedule while adhering to best software development practices
• Continuous obsession for staying informed on contemporary technologies, tools, libraries, services, frameworks, or breakthroughs that could benefit the team
• Discipline using generative AI tools in day-to-day work

What Will Make You Standout (Preferred Qualifications)

• Bachelor’s  or master's degree in Computer Science, Data Science, or a related field
• Senior level software development talent and up
• Proven track record being a technical leader in high-performing data engineering teams
• Intimate knowledge of scaling “big data” solutions in cloud-based environments
• Hands on experience deploying and maintaining software such as Hadoop, Spark, Airflow, DBT, Dagster, Temporal, Presto/Trino, Iceberg, AlloyDB, Postgres, HBase, BigQuery, BigTable, Fabric, Hive, RedShift, S3, GCS, etc.
• Experience building event-driven architectures with streaming tools such as Kafka, NATS, GCP Pub/Sub, Kinesis, Bufstream, Flink, Beam
• Knowledge of managed or hosted data solutions such as Databricks, Snowflake, ClickHouse, Tinybird, etc
• Practical knowledge working with data in formats like Parquet, Avro, Protobuf, time series, text, image, video
• Working closely to support AI/ML-focused teams (knowledge of MLflow and Ray is a big a plus)
• Comfort building internal dashboards and data-focused visualizations

What Makes Verse a Great Place to Work? 

• Lead with Empathy: We lift each other up with humility and kindness, always putting colleagues and customers first
• Be Honest & Transparent: We prioritize effective communication to build trust with our team, customers, and stakeholders
• Move with Balance & Precision: We believe speed and perseverance must be accompanied by thoughtfulness and reflection
• Leave the World a Better Place: We are passionate about our mission, and we strive to create a sustainable world for future generations

Base Pay Range

$180,000 - $250,000+

This is the estimated base salary range for this position, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to level, skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs.

Benefits and Employee Perks 

• Competitive compensation and equity grant at a high-growth start up 
• Comprehensive benefits package including medical, dental and vision insurance, and 401k 
• Flexible hours and unlimited PTO 
• Diverse and inclusive working environment 

Verse is an equal opportunity employer. All applicants and employees are considered for hire, promotion, and compensation without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, marital or familial status.

While candidates in the listed location(s) are encouraged for this role, candidates in other US locations will be considered. #LI-REMOTE

As a Solutions Architect on the Digital Natives team, you will work with the leading data engineering, data science & ML teams in the market to push the boundaries of what big data architectures are capable of. 

Reporting to the Field Engineering Manager, you will collaborate with strategic customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.

We are looking for high technical aptitude individuals with a deep sense of ownership and a desire to help customers ship solutions at production scale. Ideal candidates are deeply curious, capable of operating with confidence in ambiguous situations, and are extremely adaptable. 

The impact you will have:

• You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
• Drive technical discovery and solution design, focusing on winning competitive deals and accelerating time-to-value in strategic accounts.
• Continuously research & learn new technologies and their implementations on Databricks
• Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
• Collaborate with your fellow Solutions Architects, using your skills to support each other and our customers
• Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.
• Work closely with account executives to create and execute account penetration strategies, focusing on winning technical decision-makers and building new customer champions.
• Build trusted advisor relationships with senior and executive stakeholders by articulating the business value of Databricks in clear, outcomes-driven terms.
  
  

What we look for:

• 5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
• Experience building distributed data systems
• Comfortable programming in, and debugging, Python and SQL
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Expertise in one of the following:
• Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
• Strong executive presence with the ability to influence C/VP-level stakeholders and align technical solutions to strategic business priorities.
• Available to travel to customers in your region
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Nice to have: Databricks Certification
  
  

NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply. We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.

FEQ127R13

While candidates in the listed location(s) are encouraged to apply for this role, exceptionally well-qualified candidates in other East Coast locations will also be considered.

Mission

Solutions Architects at Databricks lead the growth of the Databricks Data Intelligence Platform. As a team, we have expertise in cloud platforms, data engineering, data analytics, and data science, machine learning, and AI. As a member of our team, you will exercise and grow your expertise in those areas, using open source projects such as Apache Spark™, Delta Lake, and MLflow. This is a customer-facing role, where you will work with customers, your teammates, the product team, our post-sales team,s and partners, to identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through the implementation, to accomplish meaningful outcomes for their businesses. In this process, you will build relationships with our customers, identify and cultivate champions, and establish yourself as a trusted advisor. You will report to a Field Engineering Manager within the Financial Services team at Databricks.

The impact you will have:

• Partner with the sales team to help customers understand how Databricks can help solve their business problems
• Provide technical leadership for customers to evaluate and adopt Databricks
• Consult on big data architecture, execute proof of concepts for strategic customer projects, and validate integrations with cloud services and other 3rd party applications
• Build and present reference architectures, how-tos, and demonstrate applications for customers
• Become an expert in, and promote open source projects (Apache Spark™, Delta Lake, MLflow, and Unity Catalog) across developer communities through meetups, conferences, and webinars
• Travel to meet with customers in your territory

What we look for:

• 10+ years in a customer-facing pre-sales role, or consulting role - preferably working with big-data technologies to solve data engineering and big-data analytical challenges
• Experience designing and architecting distributed data systems
• Comfortable programming in, and debugging, at least one of: Python, SQL, Scala, Java, or R
• Experience working with global system integrators, consulting organizations, or financial services technology, or financial services data providers is a positive differentiator 
• Experience building solutions with public cloud providers such as AWS, Azure, or GCP
• Experience with Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Experience with Data Warehousing technologies (Ex: SQL, OLTP/OLAP/DSS)
• Undergraduate degree or higher in an engineering or mathematics discipline such as Computer Science, Applied Mathematics, Electrical Engineering, etc.)

P-1399

At Databricks, we are passionate about enabling Data & AI teams to solve the world's toughest problems - from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for data interaction to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

About the Team:

The Backline Engineering Team serves as the critical bridge between Frontline Support and Engineering. We handle complex technical issues and escalations across the Data and AI ecosystem. With a strong focus on customer success, we are committed to delivering exceptional customer satisfaction by providing deep technical expertise, proactive issue resolution, and continuous platform improvements. We emphasize automation and tooling to enhance troubleshooting efficiency, reduce manual efforts, and improve the overall supportability of the platform and the health of our products. By developing smart solutions and streamlining workflows, we drive operational excellence and ensure a delightful experience for both customers and internal teams.

What your impact will be:

• Act as the ultimate technical escalation point, driving the resolution of the most complex, high-stakes customer issues on the Databricks Platform through deep analysis of core components, metrics, and logs.
• Elevate global team competency by architecting standardized troubleshooting methodologies, comprehensive runbooks, and leading deep-dive technical enablement sessions.
• Champion product supportability and observability, by actively partnering with Engineering and Product teams to influence the roadmap and integrate critical feedback.
• Spearhead strategic automation and tooling initiatives, driving programs that significantly reduce manual toil and improve global MTTR (Mean Time to Resolution) metrics.
• Act as the primary technical liaison between Support and Engineering, driving the enablement strategy for upcoming product features, architectures, and releases.
• Lead cross-functional incident response, demonstrating deep ownership and coordinating seamlessly across Engineering, Escalation, and Support teams to resolve critical requests.
• Participate in weekday and weekend on-call rotations to ensure continuous coverage.

What we look for:

We are looking for candidates who demonstrate deep mastery of one of the following and related areas:

• Application Debugging: Deep expertise in troubleshooting, supporting, and maintaining complex Java, Scala, or Python-based applications
• Big Data Ecosystems: Advanced proficiency in managing, tuning, and resolving issues within distributed computing environments, with a strong emphasis on Apache Spark™ , Hadoop or other Distributed Systems
• Database Management: Proficient at debugging, tuning, and resolving issues in SQL-based relational databases, preferably Postgres
• Automation & Tooling: Advanced proficiency in building automation frameworks and system scripts using Python or bash/shell
• Infrastructure & Networking: Deep foundation in Linux system administration, kernel-level troubleshooting, and complex network diagnostics (e.g., TCP/IP Stack, DNS, routing, packet capture analysis)
• Cloud Skills: Extensive hands-on experience debugging, optimizing, and supporting highly scalable workloads across major cloud platforms (AWS, Azure, or GCP)
• Expert-level diagnostic skills, with a proven track record of pinpointing root causes in highly complex systems through advanced black-box and system-level troubleshooting
• 12+ years of highly technical industry experience in technical support, sustaining engineering or similar roles.
• Bachelor's degree in Computer Science or related fields.

P-256

We are looking for experienced pre-sales professionals with a proven track record of helping large enterprises become more data-driven. Working with the Account Executive (AE), the Retail and CPG Sr. SA defines and directs the technical strategy for our largest and most important accounts, leading to more widespread use of our products and wider and deeper adoption of ML & AI. You will lean upon your solid background in value selling, technical account management, and technical leadership to maximize success in these accounts. While you work with a team that includes hands-on resources who will build proofs of concept and demonstrate Databricks' products, you need to be technical and must understand the relevance and application of ML & AI within a range of use cases important to the target accounts in the Retail and CPG space.

The impact you will have:

• You will work with 1-5 clients as the main technical voice for Databricks
• You will lead your customers on a transformational journey, helping them to evaluate and adopt Databricks as part of their strategy
• You will implement the technical strategy in the account, with a close understanding of the strategy
• Build a movement of technical champions within the account
• Align technical strategies around Databricks solutions
• You will provide structured mentorship for other team members

What we look for:

• 5+ years of experience working in very large (> $1m ARR), from the Retail and CPG-related space
• 3+ years working in a pre-sales capacity or supporting sales activity
• Technical in big data, data science, and cloud
• An ability in data-driven business transformation and driving change with data
• 3+ years of experience with design and implementation experience in big data technologies such as Hadoop, NoSQL, MPP, OLTP, and OLAP, or full lifecycle data science solutions
• Maintain and extend production data systems to evolve with complex customer needs
• Production programming experience in Python, R, Scala, or Java
• Nice to have: Databricks Certification

LI #Remote

P-344

At Databricks, our customers challenge us with solving some of the world's toughest data problems. Our customers rely on our Solutions Architect team to understand the technologies that power our platform, the broader cloud and technology ecosystems, and how they can all be brought together to solve these problems.

Solutions Architects at Databricks lead the adoption of the Databricks Unified Analytics Platform. As a member of our team, you will sharpen your skills on open-source projects such as Apache Spark™, MLflow, and Delta Lake to advocate the Lakehouse paradigm on public cloud providers. You will gain expertise in cloud platforms, data engineering, data analytics, data science, and machine learning. In this customer-facing role, you will identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through implementations to deliver strategic business value. You will partner with the sales team to build relationships with our customers and establish yourself as a trusted advisor.

Databricks' culture thrives on collaboration and teamwork, and you will contribute your knowledge to our teams by participating in our subject matter expert groups. In this role, you will report to the Solutions Architect Leader supporting the specific business segment.

If you are a technologist interested in Data and AI, and enjoy prototyping solutions for customers, this role is for you.

The impact you will have:

• Provide technical leadership for customers to evaluate and adopt Data and AI solutions from Databricks
• Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications
• Build and present reference architectures, technical guides, and demo applications for customers
• Provide escalated support for critical customer operational issues
• Become an expert in, and evangelize Databricks driven open-source projects (Apache Spark™, Delta Lake, MLflow, Koalas) across developer communities through meetups, conferences, and webinars
• Use your strengths to help your fellow SA's, and drive cross-functional relationships across the company
• Travel to customers (up to 30%, of which 80%+ local to your region)

What we look for:

Solution Architects are customer-facing. You'll need to be comfortable communicating ideas to various audiences through presentations, whiteboarding, architecture discussions, and platform demonstrations.

• 3+ years in a customer-facing pre-sales, technical architecture, or consulting role
• Experience designing and architecting distributed data systems
• Comfortable programming in and debugging at least one of Python, Scala, Java, SQL, or R
• Have built solutions with public cloud providers, such as AWS, Azure, or GCP
• Experience in at least one of the following:
  • Data Engineering technologies (e.g., Spark, Hadoop, Kafka)
  • Data Warehousing (e.g., SQL, OLTP/OLAP/DSS)
  • Data Science and Machine Learning technologies (e.g., pandas, scikit-learn, HPO)
• [Preferred] Degree in a quantitative discipline (e.g., Computer Science, Applied Mathematics, Operations Research, etc.)
• Nice to have: Databricks Certification

P-345

At Databricks, our customers challenge us with solving some of the world's toughest data problems. Our customers rely on our Solutions Architect team to understand the technologies that power our platform, the broader cloud and technology ecosystems, and how they can all be brought together to solve these problems.

Solutions Architects at Databricks lead the adoption of the Databricks Unified Analytics Platform. As a member of our team, you will sharpen your skills on open-source projects such as Apache Spark™, MLflow, and Delta Lake to advocate the Lakehouse paradigm on public cloud providers. You will gain expertise in cloud platforms, data engineering, data analytics, data science, and machine learning. In this customer-facing role, you will identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through implementations to deliver strategic business value. You will build relationships with our customers and establish yourself as a trusted advisor.

Databricks' culture thrives on collaboration and teamwork, and you will contribute your knowledge to our teams by participating in our subject matter expert groups. In this role, you will report to the Solutions Architect Leader supporting the specific business segment.

If you are a technologist interested in Data and AI, and enjoy prototyping solutions for customers, this role is for you.

The impact you will have:

• Provide technical leadership for customers to evaluate and adopt Data and AI solutions from Databricks
• Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications
• Build and present reference architectures, technical guides, and demo applications for customers
• Provide escalated support for critical customer operational issues
• Become an expert in, and evangelize Databricks driven open-source projects (Apache Spark™, Delta Lake, MLflow, Koalas) across developer communities through meetups, conferences, and webinars
• Use your strengths to help your fellow SA's, and drive cross-functional relationships across the company
• Travel to customers (up to 30%, of which 80%+ local to your region)

What we look for:

Solution Architects are customer-facing. You'll need to be comfortable communicating ideas to various audiences through presentations, whiteboarding, architecture discussions, and platform demonstrations.

• 5+ years in a customer-facing pre-sales, technical architecture, or consulting role
• Experience designing and architecting distributed data systems
• Comfortable programming in and debugging at least one of Python, Scala, Java, SQL, or R
• Have built solutions with public cloud providers, such as AWS, Azure, or GCP
• Experience in at least one of the following:
  • Data Engineering technologies (e.g., Spark, Hadoop, Kafka)
  • Data Warehousing (e.g., SQL, OLTP/OLAP/DSS)
  • Data Science and Machine Learning technologies (e.g., pandas, scikit-learn, HPO)
• [Preferred] Degree in a quantitative discipline (e.g., Computer Science, Applied Mathematics, Operations Research, etc.)
• Nice to have: Databricks Certification

P-256

We are looking for experienced pre-sales professionals who have a successful track record helping large enterprises become more data-driven. Working with the Account Executive (AE), the Travel & Hospitality within Retail SA defines and directs the technical strategy for our largest and important accounts, leading to more widespread use of our products and wider and deeper adoption of ML & AI. You will lean upon your solid background in value selling, technical account management and technical leadership to maximize success in these accounts. While you work with a team that includes hands-on resources who will build proofs of concept and demonstrate Databricks' products, you need to be technical and must understand the relevance and application of ML & AI within a range of use cases important to the target accounts in the Retail and CPG space.

The impact you will have:

• You will work with up to 9 clients as the main technical voice for Databricks
• You will lead your customers on a transformational journey, helping them to evaluate and adopt Databricks as part of their strategy
• You will implement the technical strategy in the account, in close understanding of the strategy
• Build a movement of technical champions within the account
• Align technical strategies around Databricks solutions
• You will provide structured mentorship for other team members

What we look for:

• 5+ years of experience working very large (> $1m ARR), from the Retail and CPG related space
• 3+ years working in a pre sales capacity or supporting sales activity
• Technical in big data, data science and cloud
• An ability in data-driven business transformation, and driving change with data
• 3+ years of experience with design and implementation experience in big data technologies such as Hadoop, NoSQL, MPP, OLTP, and OLAP or full lifecycle data science solutions
• Maintain and extend production data systems to evolve with complex customer needs
• Production programming experience in Python, R, Scala or Java
• Nice to have: Databricks Certification

P-256

We are looking for experienced pre-sales professionals who have a successful track record helping large enterprises become more data-driven. Working with the Account Executive (AE), the Retail and CPG SA defines and directs the technical strategy for our largest and important accounts, leading to more widespread use of our products and wider and deeper adoption of ML & AI. You will lean upon your solid background in value selling, technical account management and technical leadership to maximize success in these accounts. While you work with a team that includes hands-on resources who will build proofs of concept and demonstrate Databricks' products, you need to be technical and must understand the relevance and application of ML & AI within a range of use cases important to the target accounts in the Retail and CPG space.

The impact you will have:

• You will work with 1-5 clients as the main technical voice for Databricks
• You will lead your customers on a transformational journey, helping them to evaluate and adopt Databricks as part of their strategy
• You will implement the technical strategy in the account, in close understanding of the strategy
• Build a movement of technical champions within the account
• Align technical strategies around Databricks solutions
• You will provide structured mentorship for other team members

What we look for:

• 5+ years of experience working very large (> $1m ARR), from the Retail and CPG related space
• 3+ years working in a pre sales capacity or supporting sales activity
• Technical in big data, data science and cloud
• An ability in data-driven business transformation, and driving change with data
• 3+ years of experience with design and implementation experience in big data technologies such as Hadoop, NoSQL, MPP, OLTP, and OLAP or full lifecycle data science solutions
• Maintain and extend production data systems to evolve with complex customer needs
• Production programming experience in Python, R, Scala or Java
• Nice to have: Databricks Certification

P-256

We are looking for experienced pre-sales professionals with a proven track record of helping large enterprises become more data-driven. Working with the Account Executive (AE), the Retail and CPG Sr. SA defines and directs the technical strategy for our largest and most important accounts, leading to more widespread use of our products and wider and deeper adoption of ML & AI. You will lean upon your solid background in value selling, technical account management, and technical leadership to maximize success in these accounts. While you work with a team that includes hands-on resources who will build proofs of concept and demonstrate Databricks' products, you need to be technical and must understand the relevance and application of ML & AI within a range of use cases important to the target accounts in the Retail and CPG space.

The impact you will have:

• You will work with 1-5 clients as the main technical voice for Databricks
• You will lead your customers on a transformational journey, helping them to evaluate and adopt Databricks as part of their strategy
• You will implement the technical strategy in the account, in close understanding of the strategy
• Build a movement of technical champions within the account
• Align technical strategies around Databricks solutions
• You will provide structured mentorship for other team members

What we look for:

• 8+ years of experience working in very large (> $1m ARR), from the Retail and CPG-related space
• 5+ years working in a pre-sales capacity or supporting sales activity
• Technical in big data, data science, and cloud
• An ability in data-driven business transformation and driving change with data
• 3+ years of experience with design and implementation experience in big data technologies such as Hadoop, NoSQL, MPP, OLTP, and OLAP or full lifecycle data science solutions
• Maintain and extend production data systems to evolve with complex customer needs
• Production programming experience in Python, R, Scala, or Java
• Nice to have: Databricks Certification

P-256

We are looking for experienced pre-sales professionals who have a successful track record helping large enterprises become more data-driven. Working with the Account Executive (AE), the Retail and CPG SA defines and directs the technical strategy for our largest and important accounts, leading to more widespread use of our products and wider and deeper adoption of ML & AI. You will lean upon your solid background in value selling, technical account management and technical leadership to maximize success in these accounts. While you work with a team that includes hands-on resources who will build proofs of concept and demonstrate Databricks' products, you need to be technical and must understand the relevance and application of ML & AI within a range of use cases important to the target accounts in the Retail and CPG space.

The impact you will have:

• You will work with 1-5 clients as the main technical voice for Databricks
• You will lead your customers on a transformational journey, helping them to evaluate and adopt Databricks as part of their strategy
• You will implement the technical strategy in the account, in close understanding of the strategy
• Build a movement of technical champions within the account
• Align technical strategies around Databricks solutions
• You will provide structured mentorship for other team members

What we look for:

• 5+ years of experience working very large (> $1m ARR), from the Retail and CPG related space
• 3+ years working in a pre sales capacity or supporting sales activity
• Technical in big data, data science and cloud
• An ability in data-driven business transformation, and driving change with data
• 3+ years of experience with design and implementation experience in big data technologies such as Hadoop, NoSQL, MPP, OLTP, and OLAP or full lifecycle data science solutions
• Maintain and extend production data systems to evolve with complex customer needs
• Production programming experience in Python, R, Scala or Java
• Nice to have: Databricks Certification

#LI Remote 

P-186

At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions.

Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world.

Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform.

We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.

Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science.

Below are some example projects:

Apache Spark™: Develop the de facto open source standard framework for big data.

Data Plane Storage: Deliver reliable and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, Azure Blob Store.

Delta Lake: A storage management system that combines the scale and cost-efficiency of data lakes, the performance and reliability of a data warehouse, and the low latency of streaming. Its higher level abstractions and guarantees, including ACID transactions and time travel, drastically simplify the complexity of real-world data engineering architecture.

Delta Pipelines: It's difficult to manage even a single data engineering pipeline. The goal of the Delta Pipelines project is to make it simple and possible to orchestrate and operate tens of thousands of data pipelines. It provides a higher level abstraction for expressing data pipelines and enables customers to deploy, test & upgrade pipelines and eliminate operational burdens for managing and building high quality data pipelines.

Performance Engineering: Build the next generation query optimizer and execution engine that's fast, tuning free, scalable, and robust.

What we look for:

• BS in Computer Science, related technical field or equivalent practical experience.
• Optional: MS or PhD in databases, distributed systems.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Driven by delivering customer value and impact.
• 8+ years of production level experience in either Java, Scala or C++.
• Strong foundation in algorithms and data structures and their real-world use cases.
• Experience with distributed systems, databases, and big data systems (Apache Spark™, Hadoop).

P-186

At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions.

Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world.

Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform.

We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.

Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science.

Below are some example projects:

Apache Spark™: Develop the de facto open source standard framework for big data.

Data Plane Storage: Deliver reliable and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, Azure Blob Store.

Delta Lake: A storage management system that combines the scale and cost-efficiency of data lakes, the performance and reliability of a data warehouse, and the low latency of streaming. Its higher level abstractions and guarantees, including ACID transactions and time travel, drastically simplify the complexity of real-world data engineering architecture.

Delta Pipelines: It's difficult to manage even a single data engineering pipeline. The goal of the Delta Pipelines project is to make it simple and possible to orchestrate and operate tens of thousands of data pipelines. It provides a higher level abstraction for expressing data pipelines and enables customers to deploy, test & upgrade pipelines and eliminate operational burdens for managing and building high quality data pipelines.

Performance Engineering: Build the next generation query optimizer and execution engine that's fast, tuning free, scalable, and robust.

What we look for:

• BS in Computer Science, related technical field or equivalent practical experience.
• Optional: MS or PhD in databases, distributed systems.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Driven by delivering customer value and impact.
• 8+ years of production level experience in either Java, Scala or C++.
• Strong foundation in algorithms and data structures and their real-world use cases.
• Experience with distributed systems, databases, and big data systems (Apache Spark™, Hadoop).

P-59

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science.

Below are some example projects:

Apache Spark™: Develop the de facto open source standard framework for big data.

Data Plane Storage: Provide reliable and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, Azure Blob Store.

Delta Lake: A storage management system that combines the scale and cost-efficiency of data lakes, the performance and reliability of a data warehouse, and the low latency of streaming. Its higher level abstractions and guarantees, including ACID transactions and time travel, drastically simplify the complexity of real-world data engineering architecture.

Delta Pipelines: It's difficult to manage even a single data engineering pipeline. The goal of the Delta Pipelines project is to make it simple and possible to orchestrate and operate tens of thousands of data pipelines. It provides a higher level abstraction for expressing data pipelines and enables customers to deploy, test & upgrade pipelines and eliminate operational burdens for managing and building high quality data pipelines.

Performance Engineering: Build the next generation query optimizer and execution engine that's fast, tuning free, scalable, and robust.

What we look for:

• BS (or higher) in Computer Science, related technical field or equivalent practical experience.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Motivated by delivering customer value and impact.
• 5+ years of production level experience in either Java, Scala or C++.
• Strong foundation in algorithms and data structures and their real-world use cases.
• Experience with distributed systems, databases, and big data systems (Apache Spark, Hadoop).

P-59

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science.

Below are some example projects:

Apache Spark™: Develop the de facto open source standard framework for big data.

Data Plane Storage: Provide reliable and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, Azure Blob Store.

Delta Lake: A storage management system that combines the scale and cost-efficiency of data lakes, the performance and reliability of a data warehouse, and the low latency of streaming. Its higher level abstractions and guarantees, including ACID transactions and time travel, drastically simplify the complexity of real-world data engineering architecture.

Delta Pipelines: It's difficult to manage even a single data engineering pipeline. The goal of the Delta Pipelines project is to make it simple and possible to orchestrate and operate tens of thousands of data pipelines. It provides a higher level abstraction for expressing data pipelines and enables customers to deploy, test & upgrade pipelines and eliminate operational burdens for managing and building high quality data pipelines.

Performance Engineering: Build the next generation query optimizer and execution engine that's fast, tuning free, scalable, and robust.

What we look for:

• BS (or higher) in Computer Science, related technical field or equivalent practical experience.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Motivated by delivering customer value and impact.
• 5+ years of production level experience in either Java, Scala or C++.
• Strong foundation in algorithms and data structures and their real-world use cases.
• Experience with distributed systems, databases, and big data systems (Apache Spark™, Hadoop).

About the role: 

Unison is seeking a Data Scientist to power the next generation of our home equity sharing platform. This role sits at the intersection of product, engineering, and investments, driving the analytical insights and machine learning capabilities that enable us to scale efficiently and profitably.

You will translate complex data into actionable intelligence, build and deploy predictive models, and partner cross-functionally to shape product strategy and portfolio performance. This is a high-impact role for someone who thrives on ownership, intellectual curiosity, and delivering work they are proud to present.

This is a hybrid position with the requirement of 3 full days (Tues-Thurs) in our San Francisco, CA office. 

Responsibilities: 

Product Analytics and Insights

• Develop a deep understanding of Unison’s equity sharing products and customer journey
• Define, track, and forecast key product and funnel metrics across acquisition, conversion, and retention
• Partner closely with Product, Marketing, and Engineering to translate business questions into scalable data science solutions
• Deliver clear, actionable insights that inform product decisions and growth strategy
  
  

Machine Learning and Predictive Modeling

• Design, train, validate, and maintain machine learning models using data such as property attributes, customer characteristics, macroeconomic indicators, and conversion data
• Enhance model performance through feature engineering, model selection, hyperparameter tuning, and ongoing monitoring
• Productionize models to ensure scalability, reliability, and performance in live environments
  Establish best practices for model governance, documentation, and lifecycle management
  
  

Quantitative Research and Portfolio Analytics

• Build cash flow models that incorporate home price dynamics, turnover assumptions, and product terms
• Forecast prepayment behavior, default rates, home price appreciation, and portfolio returns
• Identify data-driven insights that improve the portfolio’s risk-return profile
• Support strategic initiatives through rigorous quantitative analysis
  
  

Data Engineering and Infrastructure

• Build and maintain scalable applications and workflows on AWS
• Design and support data pipelines and infrastructure to enable analytics and machine learning at scale
• Write clean, efficient, and well-documented code aligned with best practices

About you: 

• Master’s degree in Quantitative Finance, Financial Engineering, Data Science, Statistics, Operations Research, or a related quantitative discipline
• Two or more years of experience in data science, quantitative finance, data engineering, or software engineering
• Strong programming skills in Python and proficiency in SQL
• Experience with or willingness to learn distributed data tools such as Hadoop and Spark, as well as AWS cloud services
• Demonstrated experience developing and deploying machine learning models
• Passion for integrating AI-driven solutions into business workflows
• It’s a bonus if: 
• Familiarity with residential real estate, mortgage markets, or structured finance is a plus
• CFA Level I or comparable level of investment knowledge is a plus

We recognize that people come with experience and talent beyond just the technical requirements of a job. If your experience is close to what you see listed here, please still consider applying. Diversity of experience and skills combined with passion is a key to innovation and excellence. Therefore, we encourage people from all backgrounds to apply to our positions. Please let us know if you require accommodations during the interview process.

Why join us? 

The Unison team draws on a deep and wide range of talent across several disciplines. Visionaries in investment management, product development, and financial technology are joined by innovative real estate and consumer finance experts creating a unique culture.

Perks of the Unison employee include: competitive salaries, 100% paid medical and dental benefits, generous PTO policy, paid parental leave program, and fantastic downtown SF and Omaha locations, as well as being an integral part of a well-funded market leader with incredible momentum.

About us:
Unison is a San Francisco-based company that is pioneering a smarter, better way to own your home. Until now, the only way to finance a home was by taking on debt. Through the Unison Agreement, we help homeowners access their equity flexibly with no monthly payments or interest. We enhance home affordability, reduce debt, and deliver a less risky way for homeowners, investors, and society to think about their most important asset - the home. For additional information, visit www.unison.com or follow us on Facebook, Instagram, LinkedIn, Twitter and YouTube.

The last few years have been record breaking for Unison. We expanded our offering to 30 states, surpassed the $5B mark in real estate investments and partnered with over 7K customers through our HomeBuyer and HomeOwner programs. This tremendous growth was recognized by the Deloitte Technology Fast500 awards two years in a row as well as being included in the most recent Forbes Fintech50.

Pursuant to California Labor Code § 432.3, the salary range for this position is $115,000 - $155,000. This range reflects the base salary that the Company reasonably expects to pay for the role. Actual compensation may vary based on factors such as relevant experience, skills, qualifications, and geographic location. Additional compensation may include bonuses, commissions, equity, or other benefits.

Unison provides equal employment opportunity to all individuals regardless of their race, age, creed, color, religion, national origin or ancestry, sex, gender, disability, veteran status, genetic information, sexual orientation, gender identity or expression, pregnancy, or any other characteristic protected by state, federal, or local law.

Location: San Francisco, Bay Area, CA
Employment Type: Contract 

About Us

Sustainable Talent provides flexible workforce solutions, connecting top-tier talent with leading global organizations. We partner with some of the world’s most innovative companies to help them scale their teams with the right expertise. This opportunity is with one of our global high-tech clients, a leader in AI-driven technology and digital transformation. Our client is at the forefront of artificial intelligence, leveraging cutting-edge data science and machine learning to solve complex challenges.

About the Role

Our client is seeking a Python Developer to develop and optimize applications that support machine learning and data science initiatives. You’ll work on building scalable data pipelines, deploying AI models, and ensuring performance and efficiency in production environments. Collaboration with data scientists and cross-functional teams will be key to transforming research into real-world solutions. If you’re passionate about AI, cloud technologies, and writing clean, efficient code, this is an exciting opportunity to contribute to cutting-edge innovation.

What You’ll Do

• Develop and optimize Python-based applications that support data science and machine learning initiatives.
• Implement and deploy machine learning models using TensorFlow, PyTorch, and Scikit-learn.
• Design and build scalable data pipelines to preprocess and transform large datasets for AI/ML applications.
• Work closely with data scientists to translate research into production-ready ML solutions.
• Develop predictive analytics and deep learning solutions to enhance business intelligence and decision-making.
• Ensure model performance optimization and scalability in production environments.
• Integrate ML models into cloud-based platforms (AWS, GCP, Azure) and microservices architectures.
• Write clean, efficient, and well-documented Python code following software engineering best practices.
• Collaborate with cross-functional teams to drive innovation and improve AI-driven products.

What We’re Looking For

• 7+ years of software engineering experience with a strong focus on Python development.
• Expertise in machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Proficiency in data manipulation and processing libraries (Pandas, NumPy, SciPy).
• Strong understanding of predictive analytics, deep learning, and AI model development.
• Hands-on experience with big data processing technologies, including Spark, Hadoop, or Databricks.
• Proficiency in cloud platforms (AWS, GCP, or Azure) and MLOps best practices.
• Experience working with databases such as PostgreSQL, MySQL, MongoDB, or NoSQL databases.
• Strong knowledge of data structures, algorithms, and software engineering principles.
• Experience with API development and integrating AI models into scalable applications.
• Proficiency in JavaScript and front-end frameworks (React, Vue, or Angular) is a plus.
• Strong problem-solving skills and ability to communicate complex technical concepts effectively.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or equivalent experience. 

Why Join Us?

• Work with a global high-tech AI-driven company leading in data science and machine learning.
• Engage in high-impact AI/ML projects that drive innovation and business intelligence.
• Competitive salary and career growth opportunities.
• We offer full benefits, flexible PTO, and amazing company culture!
• Be part of a diverse, inclusive, and collaborative work environment that fosters creativity and excellence.

How to Apply

If you’re an experienced Senior Python Developer passionate about AI, machine learning, and data-driven innovation, we want to hear from you!

Apply today by submitting your resume and a brief cover letter detailing your relevant experience.

Sustainable Talent is an Equal Opportunity Employer and is committed to fostering an inclusive workplace. We prohibit discrimination and harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other protected characteristic under applicable laws.

About Hebbia

The AI platform for investors and bankers that generates alpha and drives upside.

Founded in 2020 by George Sivulka and backed by Peter Thiel and Andreessen Horowitz, Hebbia powers investment decisions for BlackRock, KKR, Carlyle, Centerview, and 40% of the world’s largest asset managers. Our flagship product, Matrix, delivers industry-leading accuracy, speed, and transparency in AI-driven analysis. It is trusted to help manage over $30 trillion in assets globally.

We deliver the intelligence that gives finance professionals a definitive edge. Our AI uncovers signals no human could see, surfaces hidden opportunities, and accelerates decisions with unmatched speed and conviction. We do not just streamline workflows. We transform how capital is deployed, how risk is managed, and how value is created across markets.

Hebbia is not a tool. Hebbia is the competitive advantage that drives performance, alpha, and market leadership.

The Role

We are seeking our first Data Engineer, someone who can refine our data infrastructure, drive best practices for building data pipelines, and collaborate closely with both engineering and business teams to ensure every data need is met. If you are a self-starter with a proven track record of architecting end-to-end data solutions, we’d love to hear from you.

Responsibilities

• Architect, build, and maintain ETL pipelines and workflows that ensure high data quality and reliability
• Design and manage a central data lake to consolidate data from various sources, enabling advanced analytics and reporting
• Collaborate with cross-functional stakeholders (product, engineering, and business) to identify data gaps and develop effective solutions
• Implement best practices in data security and governance to ensure compliance and trustworthiness
• Evaluate and integrate new technologies, tools, and approaches to optimize data processes and architectures
• Continuously monitor, troubleshoot, and improve data pipelines and infrastructure for performance, scalability, and cost-efficiency

Who You Are

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field
• 5+ years software development experience at a venture-backed startup or top technology firm, with a focus on data engineering
• Significant hands-on experience in data engineering (ETL development, data warehousing, data lake management, etc.)
• Adept at identifying and owning data projects end to end, with the ability to work independently and exercise sound judgment
• Proficient in Python and SQL; comfortable working with cloud-based data stack tools
• Familiar with big data processing frameworks (e.g., Spark, Hadoop) and data integration technologies (e.g., Airflow, DBT, or similar)
• Experience implementing data governance, security, and compliance measures
• Strong collaboration and communication skills, with the ability to translate business requirements into technical solutions
• Prior experience in a high-growth or startup environment is a plus
• You are comfortable working in-person 5 days a week

Compensation

The salary range for this position is set between $190,000 and $250,000. This range may be inclusive of several career levels at Hebbia and will be narrowed during the interview process based on the candidate’s experience and qualifications. Adjustments outside of this range may be considered for candidates whose qualifications significantly differ from those outlined in the job description.

Life @ Hebbia

#LI-Onsite

Company Overview

Maven Robotics is building the world’s leading general-purpose AI robots.

We are currently operating in stealth and are growing the world’s best team in AI robotics. We are looking for self-starters that are the world’s best in their field, who can innovate from a deep understanding of the fundamentals, and who share our values of unwavering truth seeking and integrity, humility, curiosity, and relentless determination.

Role Description

We are looking to recruit an exceptional Software Engineer - Software Development and Machine Learning Operations to build and maintain the infrastructure that supports our software development, machine learning models, and AI operations.

In this role you will:

• Design, implement, and manage CI/CD pipelines to facilitate seamless code integration and deployment.
• Monitor and optimize system performance, availability, and security.
• Automate infrastructure orchestration and configuration management using tools such as Kubernetes, Ansible, and similar.
• Configure and maintain data infrastructure appliances.
• Troubleshoot and resolve issues related to applications, infrastructure, and deployments.
• Work closely with our development and AI teams to deliver solutions that increase efficiency and stability.

Qualifications

Must-have:

• BS or MS in software engineering, computer science, or a related field.
• Proven experience standing up a CI/CD system from scratch.
• Experience with multi-language build systems (e.g., Bazel, Bob).
• Proficiency with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
• Experience with automation tools (e.g., Terraform, Ansible, GitHub Actions, Jenkins) and version control systems (e.g., Git).
• Strong programming skills in languages such as Python, Go, or Java.
• Self-starter attitude with strong ability to identify problems, prioritize them, then plan and execute working solutions.
• Enthusiasm for working in a fast paced startup environment and eagerness to support the team on a variety of topics.

Nice-to-have:

• Experience with MLOps platforms (e.g., MLflow, Kubeflow, or SageMaker).
• Knowledge of big data technologies (e.g., Hadoop, Spark, or Kafka).
• Experience with monitoring and observability tools (e.g., Prometheus, Grafana, ELK stack).
• Understanding of machine learning frameworks (e.g., TensorFlow, PyTorch, or Scikit-Learn).
• Experience with edge computing and IoT device management.
• Knowledge of security best practices and compliance standards in AI/ML environments.
• Proficiency in database management systems (e.g., PostgreSQL, MongoDB, or Cassandra).
• Experience with infrastructure-as-code tools (e.g., CloudFormation, Pulumi).
• Knowledge of GitOps practices and tools (e.g., ArgoCD, Flux).

We are hiring for one of our ecosystem projects, an innovative AI and Web3 company building an Ethereum Layer 2 solution integrated with advanced AI agents. As the first engineer dedicated to this initiative, you will play a pivotal role in its development, with potential opportunities to build and lead a team in the future.

Key Responsibilities

• Design and implement AI platforms, encompassing both front-end interfaces and back-end services.
• Collaborate with other developers and AI engineers on data preprocessing, model training, and optimization.
• Deploy AI models into production environments, ensuring performance, scalability, and reliability.
• Develop and maintain data processing pipelines to ensure data quality and consistency.
• Stay updated on AI technology trends, advocating for the integration of new technologies into our products.
• Contribute to other projects based on the company’s product development progress

Requirements

• Bachelor’s degree or higher in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
• 5 years of full-stack development experience, proficient in both front-end and back-end technologies.
• Expertise in front-end and back-end technologies (especially Golang)
• Eager to explore and could use new technologies related to AI that help improve working efficiency
• Strong curiosity and willingness to explore new product directions, identify potential AI applications, and contribute to product innovation.
• Familiarity with Web3, blockchain, and the crypto industry, with insights into different product models and a personal perspective on industry trends and innovations.
• Excellent communication skills and a collaborative team spirit, with the ability to independently solve problems and take initiative.

Preferred Qualifications

• Knowledge in data processing and analysis will be a plus, with knowledge of SQL and NoSQL databases such as MySQL, PostgreSQL, or MongoDB.
• Experience in deploying and optimizing AI agent
• Experience contributing to open-source projects
• Build high-performance APIs and microservices to support large-scale Web3 application
• Familiarity with large-scale data processing technologies such as Hadoop or Spark.