Job Title: Machine Learning Engineer, Motion Planning & Prediction
Location: Austin, TX
Salary Range: $120,000 - $170,000 Per Year
Job Type: Direct Hire

Sponsorship: Yes, Company provides visa sponsorship

Job Overview

A leading autonomous mobility company seeks a creative Machine Learning Engineer for motion planning and prediction in autonomous vehicles. You will design deep learning models using transformers to process petabytes of driving data, enabling safe navigation through complex environments. This role focuses on behavioral prediction, real-time inference on embedded hardware, and collaboration across engineering teams.

Key Responsibilities

• Design, train, and deploy state-of-the-art machine learning models for behavioral prediction and motion planning.

• Develop robust data pipelines to process, clean, and label massive-scale vehicle sensor and simulation datasets.

• Work with deep learning architectures such as transformers to model complex temporal interactions between traffic agents.

• Establish and own metrics for model performance, creating evaluation frameworks that correlate with on-road safety.

• Collaborate with software engineers to integrate and optimize models for real-time inference on vehicle hardware.

• Stay current with research in machine learning, imitation learning, and reinforcement learning to apply novel techniques.

Requirements

• Strong proficiency in Python and hands-on experience with modern deep learning frameworks like PyTorch, TensorFlow, or JAX.

• Solid understanding of machine learning fundamentals, including neural network architectures, training methodologies, and evaluation techniques.

• Experience with the full machine learning lifecycle, from data exploration and prototyping to deployment and monitoring.

• Proficiency in C++ for writing high-performance model inference code.

Preferred Qualifications

• Strong track record in ML competitions like Kaggle or contributions to major open-source ML projects.

• Experience applying ML to robotics problems, such as behavioral prediction, motion planning, or computer vision.

• Experience with MLOps tools and platforms like MLflow, Kubeflow, or Weights & Biases.

• Experience with large-scale distributed data processing and training frameworks like Spark or Ray.

• Publications in top-tier ML or robotics conferences such as NeurIPS, ICML, CVPR, ICLR, CoRL, or RSS.

Benefits

• Employer-subsidized healthcare (medical, dental, vision)

• Pre-tax commuter benefits

• Flexible Spending Account (FSA)

• Employer-covered disability and life insurance

• 401(k) retirement plan

• Generous PTO

• Covered lunches and more