About Stack
At Stack, we are focused on AI advancements across diverse technical domains, transforming how AI is applied in the physical realm. Our solutions are designed to navigate and understand the world with unprecedented safety, reliability, and efficiency, transforming how modern industries operate. Our decades of expertise spans diverse AI applications reflecting our commitment to exploring new frontiers and delivering excellence in AI technology.
What We're Looking For:
We are looking for an expert ML researcher/engineer to develop state-of-the art deep learning/machine learning models to improve our perception solutions under challenging and diverse driving scenarios. The ideal candidate has a strong mathematical background, extensive research experience, and a practical, product-focused mindset to produce highly performant safety-critical perception solutions.
What Success Looks Like:
- Research and develop state-of-the-art deep learning / machine learning approaches to efficiently and robustly perceive the world for a self-driving system.
- Own delivery of perception modules that provide solutions to hard on-vehicle autonomy problems.
- Guide the software development from prototype to production, including training and analysis on large-scale data sets, as well as deploying production-ready solutions on a real-time AV platform.
- Capable of leading technical topics, influencing others, building consensus, and making progress on ambiguous technical problems.
- Comfortable deploying models to production with resource constrained environments.
Required Qualifications:
- Extensive experience in Computer Vision, Machine Learning, Deep Learning, or other relevant areas of Artificial Intelligence (as evidenced by industry experience or publication record).
- Track record of driving deep learning applied research projects from start to completion, including conception, problem definition, experimentation, iteration, and finally publication or productization.
- Excellent cross-team collaboration skills.
- Extensive experience in deep learning frameworks (e.g., PyTorch, TensorFlow).
- Excellent software engineering skills in Python and / or C++.
Preferred Qualifications:
- PhD in machine learning, computer vision, robotics, or related field.
- Experience in deploying perception algorithms and models into real-world environments.
- Prior related industry experience (autonomous vehicles or robotics).
- Strong publication record in top-tier conferences in any area related to machine learning.
#LI-JG1We 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.
