Offer summary

Qualifications:

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field, 5+ years of experience, including GPU programming and optimization.

Key responsabilities:

Develop efficient model export, optimization, profiling solutions

Collaborate with cross-functional teams

Stay updated with latest ML technologies

Identify and resolve performance bottlenecks

Promote engineering excellence within the team

Job description

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.

About the Team:

The training and deployment team, part of the ML Platform org at Stack AV, is responsible for the platform that helps the AI team to build models, optimize, test, and deploy them on the autonomous vehicles.

Position Overview:

We are seeking an experienced and hands-on engineer for our ML acceleration team. The ideal candidate will have a deep understanding of GPUs and optimization, excellent collaboration skills, and the ability to drive technical excellence.

The team responsibilities include:

Analyze and profile ML models to identify performance bottlenecks.
Use OSS tooling to enhance our platform to enable ML engineers to profile models and optimize them (e.g., through quantization).
Automate the process of exporting the model to optimized format (e.g., TensorRT) and deploying them. This including transformer-based models such as VLM models.
Implement optimizations using CUDA, Triton, and custom kernels.
Collaborate with ML researchers to balance model accuracy and speed.

Key Responsibilities:

Develop and implement efficient model export, optimization, and profiling solutions to enhance performance and streamline deployment of machine learning models across various hardware platforms.
Collaboration: Collaborate with cross-functional teams to understand data requirements and design appropriate solutions.
Technology Stack: Stay updated with the latest technologies and trends in ML inference and ML accelerators.
Performance Optimization: Identify and resolve performance bottlenecks in models.
Promote Engineering Excellence: Maintain a high bar for engineering excellence in their own work but also set a culture of engineering excellence within the team.

Qualifications:

Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Experience: 5+ years of experience (including experience with GPU programming and optimization).
Technical Skills:

Strong programming skills in C++ and Python
Proven experience in GPU programming and optimization
Familiarity with deep learning frameworks, especially PyTorch
CUDA programming
Triton language for GPU kernels
PyTorch optimization techniques
TensorRT implementation
ONNX model conversion and deployment
Custom GPU kernel development
Deep understanding of GPU architectures and performance optimization

Problem-Solving: Strong analytical and problem-solving skills.
Communication: Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

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.

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