Principal AI/ML Engineer

Jobtailor; Sunnyvale (CA); On-site; USD 180,000 - 280,000; Full time

Job summary

Jobtailor in Sunnyvale, CA seeks a senior technologist to define the vision and architecture for trajectory generation systems used in autonomous driving and to lead ML-based models for complex, dynamic environments.

You will architect scalable training pipelines from large-scale driving data and simulation environments, guide real-time deployment with strict latency and safety requirements, and mentor engineers to advance next-generation embodied AI architectures for driving.

Qualifications

• MS or PhD in Computer Science, Robotics, Machine Learning, or related field.
• Experience leading technical teams delivering production ML systems.
• Deep expertise in robotics planning and control, imitation learning or reinforcement learning, generative models, or large-scale ML systems.
• Strong software engineering skills (Python, C++, or similar)
• Experience deploying ML models into real-world or safety-critical environments
• Demonstrated ability to define architecture and drive large technical initiatives across teams

Responsibilities

• Define and drive the technical vision and architecture for trajectory generation systems used in autonomous driving.
• Lead the development of ML-based trajectory generation models capable of handling complex and dynamic driving environments.
• Architect scalable training pipelines using large-scale driving datasets and simulation environments.
• Guide the integration of trajectory generation models into real-time onboard systems with strict latency and safety requirements.
• Influence the design of next-generation embodied AI architectures for driving.
• Mentor senior engineers and help develop the next generation of technical leaders.
• Raise the bar for engineering excellence, modeling rigor, and production-quality systems.
• Foster a culture of innovation, ownership, and collaborative problem solving.
• Lead complex technical initiatives spanning multiple teams across the autonomous driving stack.
• Collaborate closely with teams working on data, perception, simulation, safety validation, onboard systems.
• Define roadmaps and priorities aligned with product milestones and safety goals.
• Drive solutions from research prototypes through production deployment

Skills

Technical leadership

Trajectory generation

ML systems

Python

C++

Robotics

Large-scale ML systems

Architecture

Team mentoring

Education

MS or PhD in Computer Science, Robotics, Machine Learning, or related field

Job description

• Define and drive the technical vision and architecture for trajectory generation systems used in autonomous driving
• Lead the development of ML-based trajectory generation models capable of handling complex and dynamic driving environments
• Architect scalable training pipelines using large-scale driving datasets and simulation environments
• Guide the integration of trajectory generation models into real-time onboard systems with strict latency and safety requirements
• Influence the design of next-generation embodied AI architectures for driving
• Mentor senior engineers and help develop the next generation of technical leaders
• Raise the bar for engineering excellence, modeling rigor, and production-quality systems
• Foster a culture of innovation, ownership, and collaborative problem solving
• Lead complex technical initiatives spanning multiple teams across the autonomous driving stack
• Collaborate closely with teams working on data, perception, simulation, safety validation, onboard systems
• Define roadmaps and priorities aligned with product milestones and safety goals
• Drive solutions from research prototypes through production deployment

Requirements

• MS or PhD in Computer Science, Robotics, Machine Learning, or related field
• Experience leading technical teams delivering production ML systems
• Deep expertise in one or more areas: robotics planning and control, imitation learning or reinforcement learning, generative models, large-scale machine learning systems
• Strong software engineering skills (Python, C++, or similar)
• Experience deploying ML models into real-world or safety-critical environments
• Demonstrated ability to define architecture and drive large technical initiatives across teams