Software Engineer II Perception State Estimation

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.

Ready to make your application Please do read through the description at least once before clicking on Apply.

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 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 Bayesian filters, graph models, and deep learning 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, lane line temporal smoothing, perception based road shape generation, and open world scene tracking and state 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.

What you’ll do :

• Develop machine learning models and Bayesian algorithms for multi-object tracking, state estimation, and uncertainty estimation.
• Develop deep learning models with temporal fusion for scene state estimation including occupancy, visibility, motion (velocity), and uncertainty.
• Develop estimation algorithms for road feature estimation such as lane lines and speed limit as well as estimating the road shape.
• 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 :

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 2+ years of relevant experience (or Master's degree and 0+ years of relevant experience, or PhD).
• Relevant 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 multi-object tracking systems using classical algorithms or machine learning algorithms.
• Strong experience in deep learning, Bayesian filtering, and optimization algorithms.
• Proven experience in shipping perception software products to industry or consumers.
• At least 2 years of development experience in Python / C++ environment.

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-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 and Adoption / Surrogacy support program.
• Paid medical leave.
• Unlimited vacation and 15 paid holidays.
• Complimentary daily lunches, beverages, and snacks for onsite employees.
• Pre-tax spending accounts for healthcare and dependent care expenses.
• Pre-tax commuter benefits.
• Monthly wellness stipend.
• Backup child and elder care program.
• Professional development reimbursement.
• Employee assistance program.
• Discounted programs that include legal services, identity theft protection, pet insurance, and more.
• Company and team bonding outlets : employee resource groups, quarterly team activity stipend, and wellness initiatives.

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire.

Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

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