Machine Learning Engineer

About This Role

This role will develop and implement cutting-edge machine learning solutions for autonomous driving, focusing on evaluation systems and benchmarks for foundational models. You will collaborate with cross-functional teams to integrate disruptive AI technologies into real-world autonomous systems.

Responsibilities

• Collaborate with a creative team to develop state-of-the-art foundation models utilized in autonomous vehicle systems and simulation environments
• Lead the design and implementation of end-to-end evaluation systems and benchmarks for foundation models, encompassing pretraining, fine-tuning, and reinforcement learning stages
• Partner across organizational boundaries to integrate innovative AI technologies into production environments
• Extend and optimize large-scale data processing and evaluation pipelines to support model training and assessment
• Contribute to research and development efforts in areas such as reinforcement learning, generative modeling, and Bayesian inference
• Ensure the safety, quality, and realism of AI agents through rigorous evaluation and testing frameworks

Requirements

• Master's degree or PhD in Computer Science, Electrical Engineering, or a related technical field
• Minimum of 5+ years of experience in machine learning engineering and applied deep learning
• Proven track record with shipped products or publications in relevant areas
• Experience working with large-scale distributed systems
• Proficient in programming languages such as Python and C/C++
• Strong analytical, problem-solving, and debugging skills

Qualifications

• Master's degree or PhD in Computer Science, Electrical Engineering, or a related technical field
• Minimum of 5+ years of experience in machine learning engineering and applied deep learning

Skills

* Required skills

Benefits