Senior ML/Infra Engineer for Autonomous Vehicle AI

Overland AI; Seattle (WA); On-site; USD 120,000 - 300,000; Full time

Benefits offered by this job

Equity compensation

Best-in-class healthcare

Flexible PTO

401k with company match

Parental leave

Job summary

Overland AI in Seattle is seeking an experienced engineer to design infrastructure for training, evaluating, and deploying ML models for autonomous vehicles. You will write software to enable high-quality labeling, and build data pipelines, dashboards, and visualization tools for model evaluation.

You will manage on-prem and cloud infrastructure, leverage CI/CD to accelerate the ML lifecycle, and collaborate with Perception and Behavior Planning to advance field-ready AI for defense applications.

Qualifications

• BS CS/Engineering or related field with 5+ years of relevant experience.
• Strong Python programming skills with unit and integration testing.
• Solid understanding of data processing pipelines for ML model training.
• Experience with batch processing tools (Spark, Beam, Ray).
• Experience with data stores such as MinIO, Postgres, Redshift/BigQuery.

Responsibilities

• Design and implement infrastructure to train, evaluate, and deploy ML models for autonomous vehicles.
• Develop data processing pipelines, dashboards, and visualization tools for model evaluation and dataset insights.
• Create distributed workflows for data processing, training, and evaluation (on-prem and cloud).
• Manage on-prem and cloud infrastructure, including data storage and compute resources.
• Apply CI/CD practices to streamline the ML lifecycle and collaborate with Perception and Behavior Planning.

Skills

Python

Data pipelines

ML infra

CI/CD

Team ownership

Education

Bachelor's degree in CS/Engineering

Tools

Spark

Beam

Ray

MinIO

Postgres

Redshift/BigQuery

Job description

Overland AI in Seattle is seeking an experienced engineer to design infrastructure for training, evaluating, and deploying ML models for autonomous vehicles. You will write software to enable high-quality labeling, and build data pipelines, dashboards, and visualization tools for model evaluation.

You will manage on-prem and cloud infrastructure, leverage CI/CD to accelerate the ML lifecycle, and collaborate with Perception and Behavior Planning to advance field-ready AI for defense applications.