Machine Learning Engineer (Autonomous Driving)

Location: Hybrid, based in Sunnyvale, California, USA (preferred), or London, UK; some travel is required to support customer programmes.

Salary: $370,040–$419,760 annually.

Company

hirify.global develops an AI platform for autonomous driving, using an end-to-end, mapless, hardware-agnostic approach to support vehicle autonomy from L2+ through L4 with global OEM partners.

What you will do

• Design and train ML models that generalize across vehicle platforms, including conditioning and augmentation for vehicle kinematics and camera parameters.
• Create benchmarks and metrics for cross-platform performance and translate results into decisions for model and platform teams.
• Root-cause on-road issues such as late turns, lane-keeping, and steering problems across sensors, data, models, and actuation.
• Collaborate with controls, calibration, OEM, Driving Core, and application engineering teams to identify high-impact model improvements and move research into production.
• Support customer programmes with some travel.
• Mentor teammates and raise the standard of ML engineering across the team.

Requirements

• Several years of experience building and shipping ML systems in PyTorch and Python, including training at scale, debugging experiments, and rigorous evaluation.
• Strong robotics or automotive experience in state estimation, sensor fusion, calibration, vehicle dynamics, or controls.
• A systems perspective with the ability to trace problems through sensors, data, models, and actuation.
• Experience working with real-world, multi-sensor driving or robot data.
• Clear communication across teams and comfort owning ambiguous problems from start to finish.

Nice to have

• Experience with end-to-end or learned driving and planning policies, imitation learning, or reinforcement learning.
• Experience with platform bring-up or deployment across multiple vehicles.
• C++ skills and experience with on-vehicle or embedded deployment.

Culture & Benefits

• Hybrid working with in-person collaboration and focused remote work, plus access to vehicle workshops and labs.
• Relocation support and visa sponsorship where applicable.
• Meaningful equity and annually benchmarked salaries.
• Learning and development support.
• Location-dependent health, family, retirement, and wellbeing benefits.
• An evolving, ownership-oriented environment where processes are still being developed.

Hiring process

• Initial recruiter screen: 25 minutes.
• Hiring-manager discussion: 45 minutes, followed by approximately four hours of deep-dive technical interviews.
• Final interview focused on mission and values alignment: one hour.