About
With customers at its core, Stack AV is focused on revolutionizing the way businesses transport goods, designing solutions to alleviate long-standing issues that have plagued the trucking industry including driver shortages, lagging efficiency in uptime per vehicle, overarching safety concerns, high operating costs, and elevated emission levels. By building safe and efficient autonomous trucking solutions, Stack AV is creating better and smarter supply chains for its partners, improving business outcomes for its customers, delivering goods to end-users faster, and ultimately moving the trucking industry forward.
The Auto Labeling team develops trained algorithms, tools and infrastructure to provide labels that can be used by Perception, Motion Planning, and other ML teams for training and evaluation. The team works closely with manual labeling efforts and infrastructure to create a data centric ecosystem needed to develop real time, safety critical ML models for autonomous driving.
We are looking for a technical lead manager for the Auto Labeling team. Candidates should have a strong background in architecting, training, and deploying Deep Learning Models for Perception or Prediction, and experience in data centric model development. They should have a mission-driven mindset to deliver a product, which entails significant cross-functional interaction, and customer-centric obsession to deliver what ML teams at Stack AV need.
What We’re Looking for:
- Build and lead a team of engineers to develop state of the auto labeling tools for self driving vehicle systems.
- Set the technical direction for the team, and work cross-functionally to develop safe systems.
- Define the strategy and roadmap for automatic data labeling of autonomous driving datasets.
- Drive execution of the team’s roadmap, review their code and SW architecture, and deliver features in lockstep with key partners.
- Define labeling and dataset requirements, in close collaboration with manual labeling teams and ML modeling teams across Perception, Prediction, Planning, and other autonomy teams.
What Success Looks Like:
- BS/MS/PhD in Computer Science or related field, or equivalent industry experience (5+ years of experience).
- Experience with strong, hands-on leadership of a team of engineers.
- Understands state of the art in pseudo labels, self supervised learning and unsupervised learning.
- Familiar with techniques such as vision transformers, large foundation models, models such as Segment Anything Model.
- Experience with architecting, training, and deploying Deep Learning Models.
- Familiarity with offline perception models and acausal information for auto labeling.
- Fluent in python, C++ fluency is a plus.
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.
