Senior Software Engineer - Scalable Machine Learning

Senior Software Engineer - Scalable Machine Learning

Pittsburgh, PA, Palo Alto, CA, Detroit, MI

Latitude AI ( lat.ai ) develops automated driving technologies, including L3, for Ford vehicles ’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering –
all dedicated to making a real, positive impact on the driving experience for millions of people.

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

In the Intelligent Systems team, we convert photons into understanding, primarily via computer vision and machine learning. Our organization is responsible for all downstream tasks of the vehicle sensor suite onboard, as well as the full offboard/cloud infrastructure for machine learning at Latitude.

What you’ll do:

Scaling our machine learning models with data is vital to achieve optimal performance and to enable a safer and more sustainable future of transportation. In the Scalable ML team, we are looking at methods to improve the efficiency of model training, enabling ML developers to work efficiently with large volumes of data.

As a SWE for the Scalable ML team, you will:

• Design, and implement state-of-the-art cloud services for data ingest, workflow orchestration, and distributed training at scale
• Develop solutions to generate, manage, and process large amounts of multi-sensor training data for machine learning
• Drive advanced MLOps practices, including model artifact management, experiment tracking, and automated model deployment and testing strategies
• Collaborate closely with cross-functional teams, perception experts, and roboticists to integrate ML pipelines and ensure the delivery of high-quality, production-ready software
• Mentor junior engineers and provide technical guidance to elevate the team's software development standards

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD)
• Strong track record of successfully delivering complex software projects from conception to production
• Proven expertise in developing and optimizing machine learning data pipelines, data generation, and distributed model training
• Experience designing, building, and operating large-scale distributed systems and cloud infrastructure
• Strong proficiency in Python and/or C++ for developing high-performance, production-quality software

Nice to have:

• Master's or PhD in Computer Science, Electrical Engineering, Robotics, or a closely related field
• Hands‑on experience with distributed machine learning frameworks and tools such as Ray, PyTorch, Dagster, LakeFS, or Py Arrow
• Experience with multi‑sensor data fusion and processing techniques relevant to autonomous driving applications
• Familiarity with safety‑critical software development principles in automotive or robotics domains
• Deep understanding of machine learning concepts, computer vision use cases, and the challenges of L2/L3 autonomy

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer‑matched 401(k) retirement plan with immediate vesting
• Employer‑paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre‑tax spending accounts for healthcare and dependent care expenses
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Employee assistance program
• Discounted programs that include…