ML Engineer - RL-Driven Autonomous Driving & Simulation

Pony.ai; Fremont (CA); On-site; USD 150,000 - 250,000; Full time

Benefits offered by this job

401k plan

Life Insurance

Paid Time Off

Family Leave

Disability benefits

Free food & snacks

Job summary

Pony.ai is hiring a senior ML/AI specialist to build scalable ML systems for autonomous driving. You will design and deploy RL-based training and evaluation loops, and ship models that enhance fleet-scale performance across diverse scenarios.

The role emphasizes collaboration with Prediction, Planning, and platform teams, leveraging PyTorch and large-scale data processing to drive measurable safety and efficiency improvements.

Qualifications

• MS/PhD in CS, ML, AI or related field, or equivalent practical experience.
• Hands-on ML in production with a strong RL component.
• Depth in deep learning, sequence modeling, and generative models.
• Experience with large-scale distributed training and data processing.
• Ability to lead ambiguous technical work from framing to delivery.

Responsibilities

• Build scalable systems for training and fine-tuning large generative models for evaluation and coverage.
• Implement RL-style methods and training setups for high-fidelity behaviors in simulation workflows.
• Ship DL solutions (LLM/VLM) improving triage, automate workflows, and analyze self-driving behavior.
• Own production ML for fleet-scale assessment: training, optimization, monitoring, iteration.
• Design data + evaluation systems inspired by RLHF and related paradigms.
• Collaborate with Prediction, Planning, Research, and platform/engineering teams to land cross-cutting improvements.

Skills

RL experience

Deep learning

Generative models

Distributed training

Leadership

Education

MS/PhD in CS/ML or related field

Tools

PyTorch

Job description

Pony.ai is hiring a senior ML/AI specialist to build scalable ML systems for autonomous driving. You will design and deploy RL-based training and evaluation loops, and ship models that enhance fleet-scale performance across diverse scenarios.

The role emphasizes collaboration with Prediction, Planning, and platform teams, leveraging PyTorch and large-scale data processing to drive measurable safety and efficiency improvements.