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:
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 (Preferred):
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
We are proud to be an equal opportunity workplace. We believe that diverse teams produce the best ideas and outcomes. We are committed to building a culture of inclusion, entrepreneurship, and innovation across gender, race, age, sexual orientation, religion, disability, and identity.
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Please Note: Pursuant to its business activities and use of technology, Stack AV complies with all applicable U.S. national security laws, regulations, and administrative requirements, which can restrict Stack AV’s ability to employ certain persons in certain positions pursuant to a range of national security-related requirements. As such, this position may be contingent upon Stack AV verifying a candidate’s residence, U.S. person status, and/or citizenship status. This position may also involve working with software and technologies subject to U.S. export control regulations. Under these regulations, it may be necessary for Stack AV to obtain a U.S. government export license prior to releasing its technologies to certain persons. If Stack AV determines that a candidate’s residence, U.S. person status, and/or citizenship status will require a license, prohibit the candidate from working in this position, or otherwise be subject to national security-related restrictions, Stack AV expressly reserves the right to either consider the candidate for a different position that is not subject to such restrictions, on whatever terms and conditions Stack AV shall establish in its sole discretion, or, in the alternative, decline to move forward with the candidate’s application.
