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 TeamThe Unified Model development team is a group of highly skilled and experienced professionals who specialize in cutting-edge computer vision and machine learning technology. Together, we collaborate to create advanced, generalizable and latency-critical detection models that are capable of generating representations of static /dynamic actors, map elements, temporal attributes as well as scene representations. These representations are then utilized by various downstream autonomy consumers including motion planning, prediction, mapping and localization. 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 vision systems on vehicles.
To achieve this goal, the team constantly stays up-to-date with state-of-the-art research literature and pushes the boundaries of what is possible in an industrial setting. We are dedicated to developing cutting-edge ML algorithms and models that can help vehicles reason about the world around them in real-time, and be deployed to large-scale consumer platforms.
What You'll DoAs an Engineering Manager for Unified Modeling, you will lead and support an engineering team focused on building production-grade deep learning models for autonomous driving. You will combine team leadership with hands-on technical guidance, helping researchers and engineers translate novel computer vision methods into robust, real-time software deployed to vehicle compute.
- People Leadership & Coaching: Hire, manage, and mentor engineers across levels, running regular 1:1s, conducting performance reviews, and supporting individual career growth.
- Execution & Delivery: Own sprint planning, roadmap execution, and technical delivery of unified multi-sensor models from prototyping to 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 closely with downstream autonomy teams (Motion Planning, Tracking Prediction, Localization) to align on output formats, latency budgets, and interface contracts.
- Platform Collaboration: Work closely with adjacent infrastructure partners (ML Infra, Data Platform, Compute/HW Platform) to ensure efficient distributed training and optimized onboard runtime execution.
- Quality & Reliability: Instill high software engineering standards, reproducible ML training workflows, and comprehensive model validation suites for safety-critical automotive systems.
What You'll Need to Succeed- Education & Experience: Bachelor's degree with 8+ years of experience, Master's degree with 6+ years of experience, or Ph.D. with 4+ years of experience in Computer Science, Computer Engineering, Robotics, Electrical Engineering, or a related field.
- Leadership Experience: 2+ years of experience managing software or ML engineering teams, or 4+ years as a technical lead guiding complex machine learning perception projects.
- Machine Learning & Vision Expertise: Expert-level knowledge of deep learning architectures, computer vision, and spatio-temporal modeling using frameworks like PyTorch or TensorFlow.
- Production Deployment: Proven track record of developing and deploying computer vision models onto production or physical robotic/embedded systems.
- Software Fundamentals: Strong proficiency in Python and C++ software development, with a solid grasp of software design and testing principles.
- Collaboration & Communication: Demonstrated ability to work cross-functionally with autonomy consumers, data infrastructure teams, and systems engineers.
Nice to Have (Optional)- Ph.D. with a machine learning or computer vision focus.
- Direct experience developing autonomous vehicle perception systems or multi-sensor fusion architectures (Camera, Radar, LiDAR).
- Experience optimizing models for low-latency edge accelerators using tools like TensorRT, ONNX, or custom inference runtimes.
- Familiarity with safety-critical software standards in automotive or robotics domains.
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
- Paid medical leave
- Unlimited vacation
- 13 paid holidays
- Daily lunches, snacks, and beverages available in all office locations
- 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
Learn more about Latitude's team, mission and career opportunities at lat.ai!
The expected base salary range for this full-time position in California is $218,240 - 327,360 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude's annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.
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.
