Staff Machine Learning Engineer, Emergency Trajectory Models (Autonomous Driving)

Location: Sunnyvale, California, USA; hybrid work with regular time in the office

Salary: $336,400–$370,300 per year, plus equity

Company

hirify.global develops embodied AI software and foundation models for mapless, hardware-agnostic automated driving systems.

What you will do

• Set the technical strategy, roadmap, operating envelope, interfaces, and acceptance criteria for a learned emergency trajectory model.
• Design and train trajectory-generating policies using behavior cloning, reinforcement learning, and related sequential decision-making methods.
• Build a rare-event data strategy using fleet data, targeted mining, simulation, augmentation, and reweighting.
• Develop open-loop and closed-loop evaluations for collision avoidance, evasive steering, emergency braking, recovery, robustness, latency, and nominal-driving regressions.
• Lead integration into the shared driving stack and align decisions across simulation, evaluation, safety, and product engineering.
• Raise engineering standards through architecture reviews, mentoring, and clear communication of risks, trade-offs, and evidence.

Requirements

• Staff-level technical leadership across ambiguous machine learning programs, from research through production deployment.
• Deep expertise in learned trajectory-generation or policy models for embodied systems, including architecture, objectives, training, and empirical validation.
• Hands-on experience with behavior cloning, reinforcement learning, distribution shift, robustness, and closed-loop failure analysis.
• Strong Python and PyTorch skills and experience building reproducible training and evaluation systems for large, heterogeneous datasets.
• Exceptional technical judgment and communication, including the ability to make safety-relevant trade-offs explicit and lead without formal authority.

Nice to have

• Experience in autonomous driving or robotics, including motion planning, vehicle dynamics, control, or collision avoidance.
• Experience with fallback, redundant, mixture-of-experts, or model-routing architectures.
• Experience mining, generating, or evaluating rare events with simulation and fleet or real-world data.
• Experience deploying learned policies under real-time latency, reliability, and compute constraints; C++, CUDA, or systems optimization skills.
• Experience with multimodal, transformer-based, diffusion-based, or other generative trajectory or policy models.

Culture & Benefits

• Hybrid work combining time in offices and workshops with time working from home.
• Inclusive, diverse, and respectful working environment.
• Competitive equity package in addition to salary.
• Interview accommodations and adjustments are available when required.

Hiring process

• hirify.global supports an inclusive interview experience and can provide accommodations or adjustments on request.