- Robot type
- Autonomous Vehicle
- Location
- DetroitMichiganUSA
- Job type
- Artificial Intelligence
- Posted
- Jul 31, 2026
- Salary
- $179,200–$268,800 a year
Senior Software Engineer - ML Performance
Job description
Latitude AI ( lat.ai ) is building the future of Ford’s autonomy roadmap to make travel safer, less stressful, and more enjoyable for everyone. Bringing this vision to scale, our fully in-house developed hands-free ADAS platform will debut on the all-new Ford Fathom in 2027.
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 redefining the relationship between people and their vehicles for millions of customers.
As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at…
Job responsibilities
- Architect, design, and implement software solutions that scale from the lab to the customer, for one of the largest-scale robotics projects in history.
- Collaborate with various teams to understand, integrate and optimize their algorithms and models.
- Profile and implement efficiency improvements, from PyTorch to C++, balancing requirements with compute constraints.
- Develop infrastructure and tools which evaluate & optimize AI performance.
- Drive projects end-to-end and deliver reliable software through continuous integration, automated testing and code reviews, while in a fast-paced, highly autonomous environment which requires a strong safety culture.
Job requirements
- 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)
- Expertise in GPU/DSP architecture and heterogeneous embedded computing.
- Fluency in Python, PyTorch, ONNX, numpy, pandas.
- Fluency in modern C++, data structure optimization and parallel programming.
- Strong understanding of an AI deployment flow on an embedded platform.
- Industry experience writing production-quality, performance-critical code, and maintaining large codebases.
- Strong analytical abilities to quickly grasp concepts and design solutions.
- Strong written and verbal communication skills, to collaborate with stakeholders of various backgrounds.
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