Machine Learning Engineer (Autonomous Driving)

TL;DR

Machine Learning Engineer (Autonomous Driving): Designing and delivering ML-driven behaviors for autonomous driving systems with an accent on model architecture, data pipelines, and real-world deployment. Focus on developing end-to-end driving models, personalized driving behaviors, and scaling systems from assisted to autonomous driving.

Location: Hybrid; must be based in Sunnyvale, California or Detroit, USA

Salary: $283,500–$381,600

Company

hirify.global is a leading developer of Embodied AI technology creating mapless, hardware-agnostic AI products for automakers to accelerate the transition to automated driving.

What you will do

• Develop and improve end-to-end driving models with state-of-the-art performance and robustness.
• Lead projects on personalized and collaborative driving, including behavior conditioning and user alignment.
• Build evaluation pipelines and metrics for closed-loop and open-loop driving performance.
• Curate and mine real-world and synthetic data to drive scenario diversity and coverage.
• Influence architecture choices and training methodologies for production-scale learning systems.
• Mentor senior engineers and shape the long-term technical direction across Autonomy.

Requirements

• Extensive proven track record of shipping deep learning systems to production.
• Expertise in deep learning, specifically sequential models, control, planning, or perception.
• Proficiency in Python, C++, CUDA, and ML frameworks (especially PyTorch).
• Experience with real-time systems or robotics, ideally with simulation or vehicle-in-the-loop components.
• Ability to lead technical initiatives across teams and drive alignment.
• Must be based in Sunnyvale, California or Detroit, USA

Nice to have

• Prior work in autonomous driving, imitation learning, or trajectory prediction.
• Familiarity with personalization, human behavior modeling, or driver intent inference.
• Experience integrating ML systems into production hardware or multi-agent simulation.

Culture & Benefits

• Hybrid working policy combining office collaboration with time spent working from home.
• Core working hours to allow for a flexible individual schedule.
• Competitive equity package.
• Inclusive work environment that values diversity and new perspectives.