Machine Learning Engineer (Autonomous Driving)

Location: Sunnyvale, California, USA, or Detroit, Michigan, USA; hybrid working model

Total compensation: $311,850–$350,625 plus equity

Company

hirify.global builds an AI platform for autonomous driving using end-to-end, mapless, and hardware-agnostic driving intelligence that learns from real-world experience.

What you will do

• Develop and improve end-to-end driving models for assisted and autonomous driving.
• Lead initiatives involving personalised driving, comfort tuning, behaviour conditioning, and collaboration with user preferences.
• Build evaluation pipelines and metrics for open-loop and closed-loop driving performance and product readiness.
• Curate and mine real-world and synthetic data to improve scenario coverage and feature development.
• Integrate models across AI Platform, Simulation, Robot Software, and Model Release teams for real-world deployment.
• Lead technical initiatives, influence architecture and training decisions, and mentor senior engineers.

Requirements

• Extensive experience shipping deep learning systems to production.
• Deep expertise in deep learning, especially sequential models, control, planning, or perception.
• Strong Python skills, experience with C++ or CUDA, and proficiency with PyTorch.
• Strong software engineering foundations and experience building reliable, maintainable machine learning systems.
• Experience with real-time systems or robotics, ideally including simulation-in-the-loop or vehicle-in-the-loop components.
• Ability to lead cross-team technical initiatives, build alignment, and mentor engineers.

Nice to have

• Experience in autonomous driving, imitation learning, or trajectory prediction.
• Familiarity with personalisation, human behaviour modelling, or driver intent inference.
• Experience integrating machine learning systems into production hardware or multi-agent simulation.

Culture & Benefits

• Hybrid work combining office collaboration with focused remote work.
• Core hours and opportunities to work hands-on in vehicle workshops and labs.
• Equity participation and market-benchmarked salary reviews.
• Learning and development budgets for training, conferences, and professional growth.
• Health and dental insurance, enhanced parental leave, retirement or pension benefits where applicable, therapy access, wellbeing partnerships, and team socials.
• Relocation support and visa sponsorship are available where applicable.

Hiring process

• 30-minute recruiter screen.
• Two-hour competency interviews covering Python programming and PyTorch debugging.
• One-hour deep-dive technical interviews covering system design and machine learning, followed by a 45-minute mission and values interview.