Staff Software Engineer, ML Training Infrastructure
Job Description
Pittsburgh, PA, 15289
Description:About the Role:
In the ML Training, our mission is to provide a reliable, scalable, and easy to use training framework for modeling needs of Stack AV. In addition, this team is responsible for the overall developer experience of ML engineers including building tools for testing, validation, and understanding models and the data used to train them. Finally, we are responsible for model optimization and deployment.
Responsibilities:
Experience with both ML Platforms and building ML-based applications.
Experience building scalable, reliable infra at a fast-paced environment working with MLEs on several different modeling teams.
A deep understanding of design tradeoffs and ability to articulate those tradeoffs and work with others on getting alignment.
Experience with building ML models or ML infra in the domains of autonomous vehicles, perception, and decision making (desirable but not required).
Experience with model training, model optimization, or large data processing pipelines.
Qualifications:
Built an end to end ML model pipeline including components such as logs processing, feature extraction, dataset storage, model configuration management, model training, experiment frameworks, and serving deployment.
Shipped ML products (NLP, computer vision, recommender systems, etc.) at scale to make business impact
Knows how to build appropriate abstractions and tooling to ensure MLEs are able to rapidly iterate on models.
Prior AV experience
Company:
Stack AV
Location:
Posted:
January 09, 2026
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Description:
About Stack:
Stack is developing revolutionary AI and advanced autonomous systems designed to enhance safety, reliability, and efficiency of modern operations. Stack's autonomous technology incorporates cutting-edge advancements in artificial intelligence, robotics, machine learning, and cloud technologies, empowering us to create innovative solutions that address the needs and challenges of the dynamic trucking transportation industry. With decades of experience creating and deploying real world systems for demanding environments, the Stack team is dedicated to developing an autonomous solution ecosystem tailored to the trucking industry's unique demands.
About the Role:
