Machine Learning & Data Engineer

Responsibilities

• Develop machine learning and hybrid physics-data approaches to improve vehicle and component model accuracy.
• Develop calibration, parameter estimation, adaptive modeling, and data-driven model improvement methods across vehicle states and operating conditions.
• Build workflows that compare model predictions with test, simulation, and real-world vehicle data to identify model improvement opportunities.
• Build pipelines for ingesting, cleaning, synchronizing, transforming, storing, and accessing large-scale vehicle telemetry and time-series data.
• Develop cloud-based infrastructure for data processing, model training, simulation, evaluation, and validation.
• Build tools and workflows for dataset management, model evaluation, experiment tracking, and reproducible model development.
• Support data processing, model evaluation, and analysis workflows for vehicle intelligence.

Benefits

• The interview process includes application review, coding test, two interviews, offer negotiation, and hiring, with procedures subject to variation.
• Applications must be submitted in PDF format and under 30MB.
• The employer encourages 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 ADA.
• 42dot is an equal opportunity employer.