Software Engineering Manager II - Unified Modeling (Machine Learning)
Latitude · Palo Alto, California
About this role
**Latitude AI — Software Engineering Manager II (Unified Modeling / Machine Learning)** Latitude AI (lat.ai) is building the future of Ford’s autonomy roadmap—making travel safer, less stressful, and more enjoyable. You’ll help scale Latitude’s fully in-house hands-free ADAS platform, planned to debut on the all-new Ford Fathom in 2027. As a Ford Motor Company subsidiary, Latitude operates like a startup, with engineering in Pittsburgh, Dearborn (MI), and Palo Alto (CA). You’ll work alongside experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, and systems & safety engineering. --- ### Meet the Team The Unified Model development team builds advanced, generalizable, and latency-critical detection models for autonomous driving. These models generate representations of static/dynamic actors, map elements, temporal attributes, and scene representations—used by downstream autonomy systems such as motion planning, prediction, mapping, and localization. The goal: take algorithms from lab to road by optimizing for onboard performance and deploying production-grade vision systems. --- ### What You’ll Do - **People Leadership & Coaching:** Hire, manage, and mentor engineers; run regular 1:1s; conduct performance reviews; support career growth. - **Execution & Delivery:** Own sprint planning, roadmap execution, and technical delivery of unified multi-sensor models—from prototyping through track and public road deployments. - **Technical Guidance:** Provide architectural and modeling guidance across spatio-temporal deep learning, multi-sensor fusion (Camera, Radar, LiDAR), and multi-task learning networks. - **Downstream Alignment:** Partner with Motion Planning, Tracking Prediction, and Localization teams to align output formats, latency budgets, and interface contracts. - **Platform Collaboration:** Work with ML Infra, Data Platform, and Compute/HW Platform partners to enable efficient distributed training and optimized onboard runtime execution. - **Quality & Reliability:** Drive high software engineering standards, reproducible ML training workflows, and comprehensive model validation for safety-critical automotive systems. --- ### What You’ll Need to Succeed - **Education & Experience:** - Bachelor’s + **8+ years**, or - Master’s + **6+ years**, or - Ph.D. + **4+ years** in CS/CE/Robotics/EE or related field. - **Leadership Experience:** **2+ years** managing software/ML teams, or **4+ years** as a technical lead on complex ML perception projects. - **Machine Learning & Vision Expertise:** Expert knowledge of deep learning, computer vision, and spatio-temporal modeling (e.g., PyTorch/TensorFlow). - **Production Deployment:** Proven experience deploying computer vision models to production or physical robotic/embedded systems. - **Software Fundamentals:** Strong Python and C++ skills; solid grasp of software design and testing. - **Collaboration & Communication:** Ability to work cross-functionally with autonomy consumers, data infrastructure, and systems engineering. --- ### Nice to Have (Optional) - Ph.D. focused on machine learning or computer vision - Experience with autonomous vehicle perception systems or multi-sensor fusion architectures (Camera/Radar/LiDAR) - Experience optimizing models for low-latency edge accelerators (e.g., TensorRT, ONNX, custom inference runtimes) - Familiarity with safety-critical software standards in automotive/robotics --- ###
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