Machine Learning Systems Engineer

About the role

Motional is seeking an engineer to build and maintain the infrastructure that powers our autonomous driving software. You will focus on the deployment and optimization of machine learning models to ensure our fleet operates safely and effectively. In this capacity, you own the design of scalable systems that support the entire lifecycle of machine learning models from initial training to decommissioning. You are responsible for improving the performance and reliability of our autonomous vehicle software stack through rigorous experimentation and monitoring. You will collaborate closely with researchers and robotics engineers to transition models from development prototypes into robust production environments. A core part of your ownership involves monitoring system metrics to proactively identify and resolve bottlenecks in model inference and data pipelines. You will play a key role in ensuring that the infrastructure maintains the high safety and reliability standards required for driverless technology. This position allows you to directly influence the architecture that powers real-world autonomous vehicle operations.

Key facts

What you'll do

• Design and implement systems that support the lifecycle of machine learning models.
• Improve the performance and reliability of our autonomous vehicle software stack.
• Collaborate with researchers and robotics engineers to transition models from development to production.
• Monitor system metrics to identify and resolve bottlenecks in model inference.
• Develop and maintain tooling for data processing, model training, and deployment automation.
• Optimize computational workflows to reduce latency and increase throughput for critical inference tasks.
• Partner with cross-functional teams to define technical requirements and system specifications.
• Build and maintain infrastructure that ensures reproducibility and version control for experiments.
• Implement observability solutions to track model behavior and system health in real time.
• Contribute to the creation of best practices and standards for machine learning engineering across the organization.

Requirements

• Professional experience in software engineering or machine learning systems within a relevant industry context.
• Demonstrated proficiency in programming languages commonly used for high-performance computing.
• Proven ability to work within a multidisciplinary team to solve complex robotics challenges.
• Strong understanding of software development principles and deployment methodologies.
• Experience with infrastructure components that support machine learning workloads is essential.
• Capacity to analyze system performance metrics and apply findings to iterative improvements.
• Commitment to maintaining code quality, documentation, and collaborative engineering standards.
• Willingness to engage with evolving project requirements and adapt technical solutions accordingly.

Skills & tools

• Machine Learning
• Robotics
• Software Engineering
• System Architecture

About the company

Motional harnesses deep industry experience in our mission to develop and deploy autonomous vehicles and to make driverless technology safe and reliable. The organization combines rigorous engineering practices with a safety-first philosophy to advance the deployment of autonomous systems. Motional operates at the intersection of software, hardware, and real-world driving scenarios to validate technology at scale. The company is dedicated to building solutions that address the complexities of urban mobility and transportation needs. This role is part of a larger effort to create dependable systems that redefine the future of driving. Professionals in this position will work alongside experts in perception, planning, and control to deliver integrated solutions. The environment emphasizes continuous learning and collaboration to tackle emerging challenges in autonomous vehicle development.

Practical notes

Full-time

Las Vegas, Nevada, United States

The role is based in Las Vegas, Nevada, requiring relocation or local candidacy for on-site engagement. This is a full-time position that demands consistent availability during standard operational hours. Travel requirements are not specified in the current source documentation. No specific visa sponsorship details are provided in the source material. There are no published deadlines for application submission in the provided source. Compensation details are not included in the source documentation. Applicants are encouraged to refer to official channels for complete hiring instructions and onboarding information. This position is integral to the continued development of autonomous vehicle infrastructure and requires dedication to technical excellence. The successful candidate will be expected to integrate seamlessly into an established engineering team.