Senior / Staff Software Engineer- ML Sensing

Latitude
Palo Alto, CA, Pittsburgh, PA, Detroit, MI, Remote$179k – $269kPosted 6 April 2026

Job Description

Latitude AI ( lat.ai ) develops automated driving technologies, including L3, for Ford vehicles at scale. We’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: The Unified Model development team is a group of highly skilled and experienced professionals who specialize in cutting-edge computer vision and machine learning technology. Together, we collaborate to create advanced detection models that are capable of generating representations of both static and dynamic actors. These representations are then utilized by various downstream autonomy consumers including motion planning, prediction, and localization. The team's primary focus is on developing compute-efficient, multi-view, multi-sensor deep learning models that can perform a wide range of tasks such as 3D object detection, lane line detection, state estimation, and scene segmentation. The ultimate goal is to take these algorithms from the lab to the road, ensuring that they are optimized for onboard performance and able to function as production-grade vision systems on vehicles. To achieve this goal, the team constantly stays up-to-date with the latest research literature and pushes the boundaries of what is possible. We are dedicated to developing cutting-edge ML algorithms and models that can help vehicles reason about the world around them in real-time. What you’ll do: Develop spatio-temporal machine learning models for detection, multi-sensor fusion, segmentation, etc. Read literature, analyze raw data, and design state-of-the-art solutions Transition solutions from the lab to the test track and public roads to ensure successful production-level implementation. Collaborate with perception experts and experienced roboticists on algorithm design, prototyping, testing, deployment, and productization Build and maintain industry-leading software practices and principles Develop clean and efficient software for perception modules interfacing with other key modules Show initiative and be a valued team member in a fast-paced, innovative, and entrepreneurial environment What you'll need to succeed: A Bachelor's or Master's Degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics, or a related field plus 7 years of industry experience. Expert-level knowledge and experience in machine learning, with a proven track record of developing and deploying deep learning solutions using PyTorch, Tensorflow, or similar frameworks Experience in developing perception systems using sensors such as Camera, Radar, and LiDAR Strong experience in computer vision, perception, and point cloud processing Proven experience in shipping computer vision software products to industry or consumers At least 5 years of development experience in Python/C++ environments. Level and title will ultimately be determined based one experience and interview performance. Nice to have (optional): Ph.D. with machine learning focus, or equivalent experience Experience developing and deploying temporal computer vision models (for instance, video activity recognition or using multiple frames for improved results on other tasks). 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-mat ... (truncated, view full listing at source)
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