Responsibilities Model Optimization:

Develop and deploy ultra-low latency Deep Learning and Machine Learning algorithms specifically tailored for Rivian ADAS and Autonomy use cases. H ardware-

Aware Design:

Research and implement hardware-aware optimization strategies, including Post-Training Quantization (PTQ), Quantization-Aware Training (QAT), kernel fusion, and model distillation to maximize throughput on embedded platforms.

Performance Profiling:

Utilize and automate deep-dive profiling tools (e.g., Torch Profile, NVIDIA Nsight) to identify bottlenecks and ensure performance consistency across weekly evaluation runs.

Cross-Functional Collaboration:

Partner with low-level software and hardware architecture teams to characterize in-house ML models on embedded platforms, optimizing them within strict compute and memory constraints.

Architectural Reasoning:

Apply a deep understanding of GPU architectures to optimize models across significantly different hardware targets, ensuring scalability across the Rivian fleet.

Workflow and Infrastructure Engineering:

Design and build automated pipelines for regular model profiling across diverse architectures to enhance organization-wide insight into execution bottlenecks.

Qualifications Education/Experience:

MS (+3 years of experience in deep learning, heterogeneous computing, and ML accelerators) or Ph.D. in Computer Science, Electrical Engineering, or a related field.

Core ML Expertise:

Deep understanding of modern model architectures, including Transformers, LLMs, VLMs and LDMs.

Optimization Skills:

Proven experience in model compression techniques: knowledge distillation, pruning, and quantization (PTQ/QAT).

Hardware Knowledge:

In-depth understanding of GPU architecture and the ability to optimize for diverse hardware specifications.

Technical Toolset:

○ Proficiency in Python and deep knowledge of PyTorch or TensorFlow. ○ Hands-on experience with Tensor

RT, AIMET, ONNX

runtimes. ○ Experience with low-level programming (CUDA kernels, C++, or BLAS subroutines) for inference logic. ○ Experience with profiling tools like torch profiler and nvidia nsight.

Leadership:

California Based Applicants:

$228,000 - $285,000 (actual compensation will be determined based on experience, location, and other factors permitted by law).

Benefits Summary:

Rivian provides robust medical/Rx, dental and vision insurance packages for full-time employees, their spouse or domestic partner, and children up to age 26. Coverage is effective on the first day of employment, and Rivian overs most of the premiums. Equal Opportunity Rivian is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender, gender expression, gender identity, genetic information or characteristics, physical or mental disability, marital/domestic partner status, age, military/veteran status, medical condition, or any other characteristic protected by law. Rivian is committed to ensuring that our hiring process is accessible for persons with disabilities. If you have a disability or limitation, such as those covered by the Americans with Disabilities Act, that requires accommodations to assist you in the search and application process, please email us at candidateaccommodations@rivian.com . Candidate Data Privacy and Technology Rivian may collect, use and disclose your personal information or personal data (within the meaning of the applicable data protection laws) when you apply for employment and/or participate in our recruitment processes (\"Candidate Personal Data\"). This data includes contact, demographic, communications, educational, professional, employment, social media/website, network/device, recruiting system usage/interaction, security and preference information. Rivian may use your Candidate Personal Data for the purposes of (i) tracking interactions with our recruiting system; (ii) carrying out, analyzing and improving our application and recruitment process, including assessing you and your application and conducting employment, background and reference checks; (iii) establishing an employment relationship or entering into an employment contract with you; (iv) complying with our legal, regulatory and corporate governance obligations; (v) recordkeeping; (vi) ensuring network and information security and preventing fraud; and (vii) as otherwise required or permitted by applicable law. Rivian may share your Candidate Personal Data with (i) internal personnel who have a need to know such information in order to perform their duties, including individuals on our People Team, Finance, Legal, and the team(s) with the position(s) for which you are applying; (ii) Rivian affiliates; and (iii) Rivian's service providers, including providers of background checks, staffing services, and cloud services. Rivian may transfer or store internationally your Candidate Personal Data, including to or in the United States, Canada, the United Kingdom, and the European Union and in the cloud, and this data may be subject to the laws and accessible to the courts, law enforcement and national security authorities of such jurisdictions. How We Use AI in

Our Hiring Process:

To ensure transparency, we want candidates to know that Rivian uses iCIMS Talent Cloud Artificial Intelligence (TCAI) and AI-enabled tools to assist with screening, reviewing, organizing and highlighting profiles and applications that match the key requirements for each role. AI does not make hiring decisions: Qualified candidate applications are reviewed by a member of our team, and all decisions throughout the process are made by humans. We use AI to support efficiency and consistency, not to replace human judgment. We are committed to a fair, thoughtful, and equitable experience for every candidate. Participation in AI profile matching is entirely voluntary. If you prefer that your profile not be used in this process, you can opt out at any time. Opting out means your profile will be excluded from automated matching and will not be surfaced for additional roles through this system. Your current application remains active and will not be affected in any way. Please note that we are currently not accepting applications from third party application services.

Qualifications:

Education/Experience:

MS (+3 years of experience in deep learning, heterogeneous computing, and ML accelerators) or Ph.D. in Computer Science, Electrical Engineering, or a related field.

Core ML Expertise:

Deep understanding of modern model architectures, including Transformers, LLMs, VLMs and LDMs.

Optimization Skills:

Proven experience in model compression techniques: knowledge distillation, pruning, and quantization (PTQ/QAT).

Hardware Knowledge:

In-depth understanding of GPU architecture and the ability to optimize for diverse hardware specifications.

Technical Toolset:

○ Proficiency in Python and deep knowledge of PyTorch or TensorFlow. ○ Hands-on experience with Tensor

RT, AIMET, ONNX

runtimes. ○ Experience with low-level programming (CUDA kernels, C++, or BLAS subroutines) for inference logic. ○ Experience with profiling tools like torch profiler and nvidia nsight.

Leadership:

Strong team player with excellent communication skills to drive complex, cross-functional efforts in a fast-paced environment. 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Senior/Staff ML Engineer, ML Acceleration and Performance