Autonomous Driving ML Platform Lead

42dot Inc.; Sunnyvale (CA); On-site; USD 133,000 - 254,000; Full time

Job summary

42dot Inc. is seeking an experienced ML Platform Engineer to lead the data platform for autonomous driving. You will shape strategy, oversee scalable data pipelines, and drive the development of a data lakehouse and ML SDKs for model training and evaluation.

You will collaborate across ML teams and cloud infrastructure, ensuring high performance, reliability and scalable data access for large-scale datasets in a rapidly evolving autonomy landscape.

Qualifications

• Bachelor's degree or higher in a technical field (CS/Engineering/Robotics).
• 7+ years in Data Engineering or ML Platform roles with leadership experience.
• Proficiency in Python and Python SDK development.
• Strong knowledge of databases (MongoDB, PostgreSQL).
• Experience with ML frameworks and distributed data loaders.

Responsibilities

• Set technical strategy and oversee high-scale data platform development for ML model training/validation.
• Build data lakehouse for autonomous driving datasets including sensor and annotation data.
• Drive Data SDK development: scene data search, dataset loading and preparation.
• Identify bottlenecks across data pipelines from processing to evaluation.
• Maintain infrastructure for Data Processing Pipeline, Database, Lakehouse and Serving.
• Collaborate with ML algorithms, ML applications, and Cloud Infra teams.

Skills

Python

ML Platform

Distributed systems

Data pipelines

Leadership

Education

Bachelor's degree in CS/Engineering/Robotics

Tools

Databricks Workflows

Apache Airflow

Hive / Delta Lake

MongoDB / PostgreSQL

PyTorch / TensorFlow

Spark

Job description

42dot Inc. is seeking an experienced ML Platform Engineer to lead the data platform for autonomous driving. You will shape strategy, oversee scalable data pipelines, and drive the development of a data lakehouse and ML SDKs for model training and evaluation.

You will collaborate across ML teams and cloud infrastructure, ensuring high performance, reliability and scalable data access for large-scale datasets in a rapidly evolving autonomy landscape.