Senior ML Platform Engineer (Autonomous Driving)

Responsibilities

• Set technical strategy and oversee development of high scale, reliable data platform to manage, visualize and serve large-scale datasets for ML model training and validation.
• Build up the data lakehouse for autonomous driving scene datasets, including the sensor data, calibration data, as well as annotation data
• Drive the Autonomous Driving Data SDK development, including scene data search, datasets preparation, dataset loading, etc.
• Dig into performance bottlenecks all along the data processing pipelines, from data processing latency, data search latency to Test Procedure (TP) coverage.
• Bootstrap and maintain infrastructure for Data Platform components-Data Processing Pipeline, Database, Data Lakehouse and Data Serving.
• Collaborate with cross-functional teams, including ML algorithm, ML application, and Cloud Infra to align ML Platforms with overall Autonomous Driving System Architecture.

Qualifications

• 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
• Solid working experience in Databases (e.g., MongoDB, PostgreSQL, etc)
• Strong understanding of modern AI frameworks (e.g., PyTorch, TensorFlow etc.), especially the principle of distributed data loader for model training
• Hands-on experience with data pipeline job orchestration with Databricks Workflows or Apache Airflow, as well as integrating data pipelines with machine learning models
• Extensive experience with data technologies and architectures such as Data Warehouse (e.g., Hive) or Lakehouse (e.g., Delta Lake)
• Experience with Apache Spark or other big data computing engines
• Excellent leadership and communication skills, with a demonstrated ability to lead technical projects

Preferred Qualifications

• Experience with autonomous vehicle sensor data (e.g., LiDAR, camera, radar)
• Experience with ML model training lifecycle (e.g., data preparation, model training / validation / deployment, etc)
• Understanding data governance principles, data privacy regulations, and experience implementing security measures to protect data
• Understanding of Large Models, like VLM

Interview Process

• Application Review - Coding Test - 1st interview - 2nd interview - Offer Negotiation - Hiring
• The screening procedures may vary depending on the position, schedule, or other circumstances.

Additional information

You will be individually notified of the screening schedule and results via the email address provided in your application.

Compensation

• $133,000 - $254,0000

Additional Information

• In accordance with fair hiring practices, do not include any personal information unrelated to your job qualifications (e.g., Social Security Number, family relations, marital status, age, photo, physical condition, place of birth, etc.) in your resume.
• All documents must be submitted in PDF format and under 30MB in size.
• We strongly encourage applications from U.S. veterans and candidates eligible for employment preference under applicable laws.
• Qualified individuals with disabilities are encouraged to apply and will receive consideration under the Americans with Disabilities Act (ADA).
• 42dot does not accept unsolicited resumes and will not pay fees for any such submissions. Equal Opportunity Statement
• 42dot is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status.

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