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Software Engineering Manager II - Unified Modeling; Machine Learning

Listing for: latitude
Full Time position Listed on 2026-11-09
Job specializations:
  • Software Development
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Software Engineer
Salary/Wage Range or Industry Benchmark: 180000 - 240000 USD Yearly USD 180000.00 240000.00 YEAR

Job Description & How to Apply Below

Position: Software Engineering Manager II - Unified Modeling (Machine Learning)
Meet the Team

Latitude AI ( lat.ai ) is building the future of Ford's autonomy roadmap to make travel safer, less stressful, and more enjoyable for everyone. Bringing this vision to scale, our fully in-house developed hands-free ADAS platform will debut on the all-new Ford Fathom in 2027.

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 redefining the relationship between people and their vehicles for millions of customers.

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 Unified Model development team

The 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 Do

As 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…
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