Software Engineering Manager II; TLM Scalable Machine Learning

Software Engineering Manager II, (Staff TLM) Scalable Machine Learning

Palo Alto, CA, Detroit, MI, Pittsburgh, PA,

Latitude AI ( lat.ai ) develops automated driving technologies, including L3, for Ford vehicles ’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:

In the Intelligent Systems team, we convert photons into understanding, primarily via computer vision and machine learning. Our organization is responsible for all downstream tasks of the vehicle sensor suite onboard, as well as the full offboard/cloud infrastructure for machine learning at Latitude.

What you’ll do:

Scaling our machine learning models with data is vital to achieve optimal performance and to enable a safer and more sustainable future of transportation. In the Scalable ML team, we are looking at methods to improve the efficiency of model training, enabling ML developers to work efficiently with large volumes of data.

In your role as the manager for the Scalable ML team, you will collaborate with perception and software experts to build solutions that scale.

• Lead and mentor a team of software engineers, driving high technical standards and continuous skill development for scalable machine learning infrastructure
• Provide technical leadership and architectural vision for the design and implementation of solutions to generate, manage, and process large amounts of multi-sensor data for machine learning
• Architect and guide the development of cloud services for data ingest, workflow orchestration, and distributed training at scale
• Drive the implementation of advanced MLOps practices, including model artifact management, experiment tracking, and automated model deployment and testing strategies
• Collaborate with cross-functional teams to integrate ML pipelines, ensuring the delivery of high-quality, production-ready software with a strong focus on reliability and stability

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 7+ years of relevant experience (or Master's degree and 5+ years of relevant experience, or PhD and 2+ years of relevant experience)
• Minimum of 7 years of experience in software development, with at least 3 years in a technical leadership or senior architect role
• Extensive experience designing, building, and operating large-scale distributed systems and cloud infrastructure for machine learning
• Proven expertise in developing and optimizing machine learning data pipelines, including data generation, management, and distributed training
• Strong proficiency in python for developing high-performance, production-quality software
• Demonstrated ability to architect complex software solutions for machine learning and autonomous systems
• Track record of successfully delivering complex software projects from conception to production, emphasizing scalability and reliability

Nice to have:

• Master's or PhD in Computer Science, Electrical Engineering, Robotics, or a closely related field
• Hands-on experience with distributed machine learning frameworks and tools such as Ray, PyTorch, Dagster, LakeFS, or Py Arrow
• Experience with multi-sensor data fusion and processing techniques relevant to autonomous driving applications
• Familiarity with safety-critical software development principles in automotive or robotics domains
• Deep understanding of machine learning concepts, computer vision use cases, and the challenges of L2/L3 autonomy

What we offer you:

• Competitive compensation packages
• High-quality individual and…