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.
What We're Looking For
We are looking for people who are passionate about delivering self-driving (L4) products that make the way we move safer, faster, and more efficient. We seek mission-driven, highly skilled people with deep experience in fast-paced, rapidly growing tech development environments. We are looking for strong Computer Vision/Machine Learning engineers to develop, train, and deploy a state-of-the-art perception pipeline for our self-driving vehicles. We seek engineers with strong foundations coupled with a practical, product-focused mindset to produce a highly performant, real-time, safety-critical application.
What Success Looks Like
- Work in a team to design and develop state-of-the-art perception systems for self-driving vehicle systems.
- Contribute to the technical direction of the team, and work cross-functionally to develop safe systems.
- Write software for perception models for real-time, resource-constrained applications.
- Develop and evaluate multimodal perception approaches for pushing performance and improving robustness.
- Identify bottlenecks and limitations in system performance, and develop novel perception components to unlock new perception capabilities and reliability.
- Drive experimentation, design, and iteration exercises, and align stakeholders with strong presentation and communication skills.
- Experience with architecting, training, and deploying Deep Learning Models.
- Experience with building perception systems using lidar, camera and/or radar data.
- Knowledge and experience of advanced probabilistic algorithms, real-time algorithms, and machine learning approaches.
- Experience with approaches to one or more perception problems, such as multi-object detection, panoptic segmentation, temporal detection, and tracking.
- Strong experience in software engineering and algorithm design.
- Fluent in Python.
- Experience with C++ or CUDA 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.
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.
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