Senior ML Engineer - Autonomous Vehicle Motion Planning

Plusai; Santa Clara (CA); On-site; USD 130,000 - 220,000; Full time

Benefits offered by this job

401(k) plan

Free lunch & snacks

Competitive salary

Job summary

PlusAI, a Physical AI company, seeks a machine learning engineer to train and deploy ML-based planning algorithms for its autonomous trucking fleet. The role is based in Silicon Valley and involves data-driven trajectory generation, behavior planning, and real-time decision making.

You will own end-to-end ML lifecycle, collaborate with runtime, perception, prediction, and mapping teams, and design validation strategies to ensure safety and production reliability within a QMS-compliant framework.

Qualifications

• BS/MS/PhD in Computer Science, Robotics, Machine Learning, or a related field.
• 4+ years of experience developing ML systems for robotics or real-time decision-making.
• Strong Python and PyTorch skills.
• Solid understanding of deep learning, sequence modeling, transformers, or diffusion models.
• Experience designing datasets, experiments, validation methodologies, and metric-driven evaluations.
• Strong software engineering skills and production-quality code.

Responsibilities

• Develop ML models for autonomous vehicle planning using map, perception, routing, and sensor data.
• Design model architectures for trajectory generation, behavior planning, and decision making.
• Own end-to-end ML lifecycle: data curation, feature engineering, training, evaluation, deployment, monitoring.

Skills

Python

PyTorch

Transformers

Deep Learning

Production Software

Data Analysis

Cross-functional team work

Debugging & troubleshooting

Education

BS/MS/PhD in CS/Robotics/ML

Tools

C++

CUDA

ONNX Runtime

TensorRT

Job description

PlusAI, a Physical AI company, seeks a machine learning engineer to train and deploy ML-based planning algorithms for its autonomous trucking fleet. The role is based in Silicon Valley and involves data-driven trajectory generation, behavior planning, and real-time decision making.

You will own end-to-end ML lifecycle, collaborate with runtime, perception, prediction, and mapping teams, and design validation strategies to ensure safety and production reliability within a QMS-compliant framework.