Staff Data Scientist, Autonomy Systems

Key Skills

Autonomous vehicles, Data Biuld Tool - dbt, Data science techniques, Design, Effective communication skills, Machine learning techniques, Presentation skills, Python Programming, Simulation software, SQL, Statistical modeling

Job Description

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.

Meet the team:

The Latitude AI Systems Engineering team brings all the components of the autonomy stack together. We work very closely with the software teams to verify all of the functions of the autonomy stack from sensing and perception through prediction and motion planning. Our team’s primary deliverable is a Safety Case based on real-world testing that is inherently data driven and statistical in nature.

We are looking for a highly skilled Data Scientist to join our Autonomy Systems engineering team. The team is responsible for defining all of the requirements and verification approaches for the functions of the autonomy stack and for the vehicle as a whole. You will work closely with autonomy engineers, systems engineers, and safety engineers to develop models and metrics to quantify the performance of our autonomy system. You will also develop the key performance metrics used in the development of new features to pinpoint any regressions before they hit the vehicle.

What you’ll do: 

• Derive novel and innovative data science, and statistical modeling solutions for applications within autonomous driving
• Develop statistical risk models for autonomous driving in complex environments, including perception, prediction and other machine learned components
• Develop models that characterize how noise and variability in an autonomy function impacts down stream functions
• Inject perception and prediction noise in simulation to demonstrate downstream robustness to upstream in range noise
• Define autonomy metrics that measure the impact of new features on the autonomy stack and improve its overall performance
• Develop the safety case argumentation from a statistical perspective
• Present results and insights to executive leadership
• Provide guidance and mentorship to other team members

What you'll need to succeed:

• PhD or Master's degree in Engineering, Computer Science, Statistics, Mathematics, or a related field
• 5+ years of experience in a data science or related field
• Ability to interpret data in the presence of ambiguity (e.g., confounding factors, data sparsity, Data quality, etc.)
• Strong background in statistical risk modeling and analysis for safety critical applications
• Creativity and adaptability regarding data science approaches that provide safety case argumentation for an Autonomous Vehicle
• Experience with robotics and machine learning 
• Experience designing metrics and forecasting system performance
• Proficient with large-scale data analysis
• Proficient with Python
• Proficient with SQL, DBT, and related database technologies
• Ability to work independently and collaboratively with cross-functional teams
• Strong communication and presentation skills

Nice to have (optional): 

• Experience in autonomous driving systems
• Experience in System Verification and Validation
• Knowledge of perception, prediction, motion planning, and/or computer vision
• Experience with simulation and resimulation