설명
The Role
The Senior Data Engineer, AI and Robotics will join the AI Research team within the Autonomous Robotics Center (ARC). This role owns the robotics data backbone that enables scalable robot learning in manufacturing — from data capture and curation through versioning, serving, and auditing. Your work will make model development reproducible, testable, and production-ready.
This is a robotics and machine learning (ML) infrastructure role, focused on multimodal robotic datasets and continuous model iteration. You will partner closely with AI researchers, robotics engineers, and plant teams to turn real-world robot behavior and failures into high-quality training data and robust production systems.
What You’ll Do
- Build and operate multimodal data pipelines for robotics (e.g., vision, depth, force/torque, joint states, events, metadata), including reliable capture from lab and plant-adjacent cells.
- Implement reproducible data logging and replay workflows (including ROS 2 bagging where applicable) to enable debugging, regression testing, and dataset construction.
- Own dataset lifecycle management, including versioning and lineage, provenance, governance, and data quality gates to support trustworthy model training and evaluation.
- Integrate experiment tracking and model/data traceability so teams can compare runs, reproduce results, and audit changes over time.
- Establish MLOps automation patterns (CI/CD/CT-style pipelines for ML) that reduce manual toil and increase deployment confidence for robotics AI updates.
- Partner with AI/ML, planning, and validation teams to define data contracts (schemas, labeling standards, failure taxonomies) and turn field failures into curated training datasets.
What You’ll Need (Required Qualifications)
- B.S. or M.S. in Computer Science, Computer Engineering, Data Engineering, or a related field.
- 6+ years of experience building production data systems and/or ML infrastructure, with practical experience supporting training pipelines end-to-end.
- Strong proficiency in Python and at least one of: C++, Scala, or Java.
- Demonstrated engineering discipline in testing, documentation, and operational reliability.
- Experience with dataset versioning, lineage, and reproducibility tooling (e.g., DVC or equivalent approaches).
- Experience with experiment tracking and model registry patterns (e.g., MLflow or equivalent tools).
- Ability to work onsite with hardware and robotics teams, and to design pipelines that handle real-world robotic logging constraints (e.g., bandwidth limits, dropped frames, timing drift).
What Will Give You a Competitive Edge (Preferred Qualifications)
- Hands-on robotics logging and replay experience (e.g., ROS 2 bags, system telemetry pipelines).
- Experience with simulation-to-real data workflows and dataset synthesis strategies.
- Familiarity with data governance requirements and auditability in safety-adjacent or safety-critical systems.
- Experience building tools to support data labeling workflows, quality assurance, and active learning loops.
다양성 정보
General Motors는 법적으로 금지된 차별을 배제하는 것은 물론 포용성과 소속감을 진정으로 장려하는 직장이 되기 위해 노력하고 있습니다. 당사는 다양성이 보장되는 환경에서 직원들이 역량을 발휘하고 우리 고객을 위한 더 좋은 제품을 개발할 수 있다고 믿습니다. 따라서 입사에 관심 있는 사람이 있다면 포지션별 주요 업무와 자격을 확인하고 본인이 보유한 기술과 능력에 부합하는 모든 포지션에 적극적으로 지원하기를 장려합니다. 지원자는 채용 과정에서 역할 관련 평가(해당하는 경우) 및/또는 채용 전 스크리닝을 통과해야 합니다. 자세한 정보는 GM 채용 과정 안내를 참고하십시오.
공평한 취업 기회 선언 (미국)
General Motors는 공평한 기회를 제공하는 고용주임을 자부합니다. 자격을 만족하는 지원자는 인종과 피부색, 성별, 성적 지향, 성별 정체성, 국적, 장애, 재향 군인 보호법 적용 여부와 상관없이 채용 후보로서 심사를 받습니다.
숙소 (미국 및 캐나다)
General Motors는 장애인을 포함한 모든 구직자들에게 취업 기회를 제공합니다. 구직이나 취업 지원에 도움이 되는 합리적인 숙소가 필요한 경우 [email protected]으로 이메일을 보내시거나 800-865-7580으로 전화주십시오. 이메일에, 귀하가 요청하는 특정한 숙소에 대한 설명과 귀하가 지원하는 직무와 채용 요청서 번호를 포함해주세요.