Senior Software Engineer - Machine Learning - Multi-Object Tracking

Latitude AI (lat.ai) is an automated driving technology company developing a hands-free, eyes-off driver assist system for next-generation 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.

The State Estimation team is a group of highly skilled and experienced professionals who specialize in cutting-edge multi-object tracking, scene estimation, and machine learning technology. Together, we collaborate to create advanced models that are capable of temporally tracking both static and dynamic actors as well as estimating road features. The State Estimation team is the interface of the perception system to various downstream autonomy consumers including motion planning, prediction, and localization.

The team's primary focus is on developing compute-efficient models and systems that can perform a wide range of tasks such as closed world multi-object tracking, track-to-detection data association, object motion forecasting, uncertainty estimation, road shape estimation. 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 perception 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 tracking algorithms, ML algorithms, and models that can help vehicles reason about the world around them in real-time. 

• →Develop spatio-temporal machine learning models for multi-object tracking and uncertainty estimation.
• →Develop machine learning models to estimate road features, lane markings, road shape and road topology
• →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 roboticist 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

• 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 in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 2+ years of relevant experience)
• Experience in developing multi-object tracking systems using machine learning models
• Relevant knowledge and experience in machine learning, with a proven track record of developing and deploying deep learning solutions using PyTorch or similar frameworks
• Strong experience in computer vision, perception, and deep learning
• Proven experience in shipping perception software products to industry or consumers
• At least 4 years of development experience in Python/C++ environment

• Ph.D. with machine learning focus, or equivalent experience. 
• Experience developing and deploying machine learning models with compute constraints.