Latitude 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.
Meet the team:
The Sim Cloud team ensures that our simulation (fully synthetic) and resimulation (replay engine using vehicle logs) workflows run efficiently and reliably at large scale. We use a mix of open source and cloud provider services to implement a processing framework that's cloud-agnostic as well as capable of running on-prem. The results of these simulations is business-critical for us - they're used in order to allow autonomy developers and testers to do large-scale safety and performance testing of changes prior to in-vehicle testing. We interact with engineers throughout the onboard and offboard stack in order to ensure smooth end-to-end capabilities.
What you'll do:
- We run vehicle simulations at unprecedented scales in order to ensure we're releasing a safe product. You'll support this via improvements to our sim/resim cloud framework and applications that run on this framework. In terms of implementation, this involves a lot of Python coding, interacting with open source packages and various AWS/GCP services. In terms of analysis, we're constantly looking for bottlenecks that limit scalability or otherwise hinder performance. You'll put together benchmarking to identify these spots and associated dashboards to track and summarize the information. Then armed with that information, you'll implement solutions to increase efficiency.
- It's not enough to have a framework that is functional - it needs to be intuitive and easy to use. We take our best guesses at this, but things evolve over time based on user interaction - both direct feedback as well as realizing how users are accidentally misusing or misinterpreting the results. Sim Cloud supports autonomy, systems, test, and a variety of other teams across the organization. Having an eye for how the system is being used, what users need, and a willingness to engage with these users on future improvements is critical.
- We also can't build it all, so we want to make the framework well-documented and as self-serve as possible for others to extend it (while being there to answer questions). For example, when there's a new portion of the autonomy stack, we want that autonomy team to be able to update resim to add it in themselves so that they can iterate quickly.
- In order to run logs through resim, we need to first know what logs are interesting. You'll contribute to the ecosystem of how we manage storing and searching for these logs efficiently, including how we automate indexing the interesting actors and interactions in a scene and how we determine our dataset coverage.
- Once we've run resim, we want to do something with the updated logs. Frequently this involves metrics to analyze the AV's performance; these metrics could range from low-level performance of a particular detector in the stack to if the AV is meeting high-level business objectives. You'll both work on the sim/resim cloud framework implementation to make this easy for all developers to add in their metrics and support the metrics implementation themselves as needs arise.
- Expertise in writing Python code that's efficient, well-documented, and well-tested
- Experience writing scalable applications that execute in a cloud or HPC environment
- Experience writing software that interacts with AWS and/or GCP services
- Familiarity with NumPy and scientific programming
- Willingness and desire to learn how onboard and offboard components interact with each other and propose solutions to improve how developers and testers work with both systems
- Bachelor's degree, Master's degree, or PhD in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field
- C++ development experience
- Experience with Kubernetes
- 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
- Paid medical leave
- Unlimited vacation
- 15 paid holidays
- Complimentary daily lunches, beverages, and snacks for in office employees
- Pre-tax spending accounts for healthcare and dependent care expenses
- Pre-tax commuter benefits
- Monthly wellness stipend
- Adoption/Surrogacy support program
- 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
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. #J-18808-Ljbffr