Senior ML Platform Engineer (Autonomous Driving)

42dot
Sunnyvale, San Francisco
Workplace: HybridFull timeUSD 133,000 - 254,000 annuallyFunction: DevOps, Cloud & InfrastructureExperience: 7+ yearsEducation: bachelorsSkills: ["Leadership","Communication","Technical project leadership"]

Build and scale the core data platform and ML training/evaluation infrastructure for autonomous driving. Own a distributed lakehouse for large scene datasets (sensor, calibration, and annotation data), develop an Autonomous Driving Data SDK, and optimize end-to-end data pipeline performance (latency and test procedure coverage). Collaborate with ML algorithm, ML application, and cloud infrastructure teams to align ML platform architecture with the overall autonomous driving system.

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FursaFursa
42dot
42dot
4 months ago

Senior ML Platform Engineer (Autonomous Driving)

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Source: Company careers pageValidated by: Fursa AI
Last checked: 20 hours agoStatus: Live

Job Summary

Build and scale the core data platform and ML training/evaluation infrastructure for autonomous driving. Own a distributed lakehouse for large scene datasets (sensor, calibration, and annotation data), develop an Autonomous Driving Data SDK, and optimize end-to-end data pipeline performance (latency and test procedure coverage). Collaborate with ML algorithm, ML application, and cloud infrastructure teams to align ML platform architecture with the overall autonomous driving system.
Location: Sunnyvale, San Francisco
Workplace: Hybrid
Employment Type: Full time
Job Function: DevOps, Cloud & Infrastructure
Seniority: Mid level

Key Responsibilities

  • •Set technical strategy and oversee development of a high-scale, reliable data platform for ML training and validation.
  • •Build the data lakehouse for autonomous driving scene datasets, including sensor, calibration, and annotation data.
  • •Develop an Autonomous Driving Data SDK for scene search, dataset preparation, and dataset loading.
  • •Investigate and address performance bottlenecks across data processing pipelines, including latency and test procedure coverage.
  • •Bootstrap and maintain infrastructure components for data processing, database, data lakehouse, and data serving; collaborate with cross-functional ML and cloud teams.

Pay and Benefits

Salary: USD 133,000 - 254,000 annually

Key Requirements

  • •Bachelor's degree or higher in Computer Science, Engineering, Robotics, or a similar technical field.
  • •Minimum of 7 years of experience in Data Engineering or ML Platform roles.
  • •Expert-level proficiency in Python and solid experience in Python SDK development.
  • •Strong working experience with databases (e.g., MongoDB, PostgreSQL).
  • •Hands-on experience building data pipeline orchestration with Databricks Workflows or Apache Airflow, integrating pipelines with ML models.
Experience:7+ yearsAutonomous drivingData engineeringML platformsMobility AIDistributed systemsData lakehouse
Education:Bachelor's
Skills:LeadershipCommunicationTechnical project leadership
Tech Stack:PythonMongoDBPostgreSQLPyTorchTensorFlowDatabricks WorkflowsApache AirflowHiveDelta LakeApache Spark

Company Brief

42dot
Develops autonomous driving and mobility software platforms, including AI-based perception, mapping, routing, and connected-vehicle technologies. It works on next-generation transportation systems and self-driving vehicle capabilities for automotive applications.
Industry: Autonomous Vehicles
Company Size: Large (251 to 1,000 employees)
Growth: Scaleup
Headquarters: Seoul, South Korea
Founded: 2019
WebsiteLinkedIn