onsite
ML Platform Engineer Autonomous Driving - 42dot
Devops Engineer
Design and build a high‑scale, reliable data platform for autonomous driving, managing millions of scenes and delivering high‑performance data serving SDKs for ML training, evaluation, and deployment in the cloud.
About the role
Key Responsibilities
- Architect and develop a distributed data platform to ingest, store, and serve millions of autonomous driving scenes for ML model training and evaluation.
- Implement high‑performance data serving SDKs in Python and C++ to support real‑time model training pipelines.
- Integrate with cloud services (AWS) and orchestrate workloads using Kubernetes for scalability and reliability.
- Collaborate with data scientists and ML engineers to optimize data pipelines, reduce latency, and improve model training efficiency.
- Monitor platform health, troubleshoot performance bottlenecks, and continuously improve system resilience.
Requirements
- Strong experience with distributed systems and large‑scale data platforms.
- Proficiency in Python and C++ for performance‑critical components.
- Hands‑on experience with AWS services (S3, EC2, EKS) and Kubernetes orchestration.
- Solid understanding of ML Ops practices, including model training, evaluation, and deployment pipelines.
- Excellent problem‑solving skills and a passion for autonomous driving technologies.
Skills
pythoncawskubernetes