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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Engineer, ML Data Services in Pittsburgh - **Company:** Energy Jobline - **Location:** Pittsburgh, PA, United States - **Experience:** Expert - **Salary:** $149,000.0 - $198,500.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Amazon S3, Big Data, Code Review, Data as a Services, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Cursor (Graphical User Interface Elements), Amazon DynamoDB, Python (Programming Language), Machine Learning, Systems Development Life Cycle, Software Engineering, GitHub Copilot, Apache Spark, Backend, Containerization, Information Technology, Api Gateway, Restful APIs, Code Restructuring, Data Pipelines, Docker, Microservices - **Published:** September 4, 2026 - **Apply:** https://www.energyjobline.com/job/senior-engineer-ml-data-services-pittsburgh-31509027 ## About the Role * 5+ years of software development experience with Python . Relevant experience with Java or Go * 5+ years of web backend development experience with REST APIs and microservices * 3+ years of AWS cloud experience (e.g., DynamoDB, API Gateway, EKS, Lambda, OpenSearch, Redshift, S3 ) * 3+ years of data engineering experience with AWS Step Functions, Airflow or Prefect * Strong written and oral communication skills * Experience working in cross-functional development teams, including quarterly road map design * Hands-on experience using modern AI coding tools (e.g., Cursor, Claude Code, GitHub Copilot) to accelerate development, refactoring, and code review. * Ability to mentor junior engineers * BS or MS in Computer Science or related field Bonus points (not required): * Hands-on experience with using Ray, Beam, Spark, or related big data processing in a large-scale environment * Experience in Docker Containerization * Autonomous driving industry experience ## Description We are seeking a Senior Engineer to join our ML Data Services team and help us build and improve data infrastructure for Autonomy ML teams. As a Senior Engineer, you will be responsible for building scalable microservices, APIs, and tooling to support Autonomy labeling needs. You will also help architect and implement scalable pipelines to process terabytes of data and deliver datasets for ML training, Simulation, and evaluation. What you'll be doing: * Design and implement Restful APIs and microservices for data labeling and annotations * Architect, build and maintain scalable data processing pipelines with cloud ETL technology to deliver datasets for Autonomy teams * Take ownership of highly-available, critical backend services and APIs that store and expose terabytes of data * Work closely with leadership and stakeholders to define objectives, align timelines, agree on key deliverables, and build the execution plan * Design and develop monitoring and observability services for the MLOps data service pipelines * Mentor and teach junior engineers in the team to develop good SDLC skills and better quality code with pairing sessions ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [7 Most Popular Web Developer Jobs in Europe](https://www.wearedevelopers.com/magazine/163-7-most-popular-web-developer-jobs-in-europe) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)