Job 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:
The mission of the Foundational Models team is twofold. Firstly, it aims to leverage the recent advances in foundational models and generative AI to improve the safety and efficiency of the Autonomy Stack developed by Stack. Secondly, it works on co-designing a new HW/SW platform to run these models and workflows. As a Staff Engineer, your role will be contributing to the design, development and maintenance of the offboard machine learning models and the pipelines and workflows to leverage these for improving the autonomy Stack and building a new HW/SW platform to efficiently train and deploy them.
Responsibilities:
- Contribute to the technical direction of the team and broader perception org on leveraging foundational models and related techniques.
- Design and implement offboard pipelines to train, distill, evaluate and serve Machine Learning Models.
- Demonstrate that these pipelines work with open source data and contribute to open-source libraries.
- Proactively identify opportunities for improvements and work with leadership team on prioritization of resolutions.
- Align stakeholders with strong presentation and communication skills.
- Lead challenging technical topics and build consensus.
Qualifications:
- BS (with 6 years of experience), MS (with 5 years of experience) or PhD (with 3 years of experience) in developing machine learning models or systems.
- Track record of driving projects from start to completion, including conception, problem definition, experimentation, iteration, and finally productization.
- Experience in contributing to or leveraging one or more of the recent advances related to foundational models such as pre-training models, RL based fine-tuning , neural rendering, diffusion based synthetic image/video generation, World Foundational Models.
- Experience with processing large datasets, training ML models in distributed environments.
- Track record of developing end to end pipelines for training Machine Learning Models
- Strong experience in Python and at least one of popular Deep Learning frameworks like Pytorch, Tensorflow, JAX.
- Nice to have: Experience with containerization, FastAPI, REST /GraphQL, SQL.
- Nice to have: Experience with autonomous driving and/or robotics.
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.
