Job Application for Research Engineer, Infrastructure, Kernels at Thinking Machines Lab Back to jobs Research Engineer, Infrastructure, Kernels San Francisco Apply Thinking Machines Lab's mission is to empower humanity through advancing collaborative general intelligence. We're building a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals. We are scientists, engineers, and builders who’ve created some of the most widely used AI products, including ChatGPT and Character.ai, open-weights models like Mistral, as well as popular open source projects like PyTorch, OpenAI Gym, Fairseq, and Segment Anything.
About
the Role We’re looking for an infrastructure research engineer to design, optimize, and maintain the compute foundations that power large-scale language model training. You will develop high-performance ML kernels (e.g., CUDA, CuTe, Triton), enable efficient low-precision arithmetic, and improve the distributed compute stack that makes training large models possible. This role is perfect for an engineer who enjoys working close to the metal and across the research boundary. You’ll collaborate with researchers and systems architects to bridge algorithmic design with hardware efficiency. You’ll prototype new kernel implementations, profile performance across hardware generations, and help define the numerical and parallelism strategies that determine how we scale next-generation AI systems. Note: This is an "evergreen role" that we keep open on an on-going basis to express interest. We receive many applications, and there may not always be an immediate role that aligns perfectly with your experience and skills. Still, we encourage you to apply. We continuously review applications and reach out to applicants as new opportunities open. You are welcome to reapply if you get more experience, but please avoid applying more than once every 6 months. You may also find that we put up postings for singular roles for separate, project or team specific needs. In those cases, you're welcome to apply directly in addition to an evergreen role. What You’ll Do Design and implement custom ML kernels (e.g., CUDA, CuTe, Triton) for core LLM operations such as attention, matrix multiplication, gating, and normalization, optimized for modern GPU and accelerator architectures. Design and think through compute primitives to reduce memory bandwidth bottlenecks and improve kernel compute efficiency. Collaborate with research teams to align kernel-level optimizations with model architecture and algorithmic goals. Develop and maintain a library of reusable kernels and performance benchmarks that serve as the foundation for internal model training. Contribute to infrastructure stability and scalability, ensuring reproducibility, consistency across precision formats, and high utilization of compute resources. Document and share insights through internal talks, technical papers, or open-source contributions to strengthen the broader ML systems community. Skills and
Qualifications Minimum
qualifications: Bachelor’s degree or equivalent experience in computer science, electrical engineering, statistics, machine learning, physics, robotics, or similar. Strong engineering skills, ability to contribute performant, maintainable code and debug in complex codebases Understanding of deep learning frameworks (e.g., PyTorch, JAX) and their underlying system architectures. Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts. A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships. Proficiency in CUDA, CuTe, Triton, or other GPU programming frameworks. Demonstrated ability to analyze, profile, and optimize compute-intensive workloads. Preferred
qualifications — we encourage you to apply if you meet some but not all of these: Experience training or supporting large-scale language models with tens of billions of parameters or more. Track record of improving research productivity through infrastructure design or process improvements. Experience developing or tuning kernels for deep learning frameworks such as PyTorch, JAX, or custom accelerators. Familiarity with tensor parallelism, pipeline parallelism, or distributed data processing frameworks. Experience implementing low-precision formats (FP8, INT8, block floating point) or contributing to related compiler stacks (e.g., XLA, TVM). Contributions to open-source GPU, ML systems, or compiler optimization projects. Prior research or engineering experience in numerical optimization, communication-efficient training, or scalable AI infrastructure. Logistics Location: This role is based in San Francisco, California.
Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD. Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
Benefits: Thinking Machines offers generous health, dental, and vision
benefits, unlimited PTO, paid parental leave, and relocation support as needed. As set forth in Thinking Machines' Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law. Create a Job Alert Interested in building your career at Thinking Machines Lab? Get future opportunities sent straight to your email. Create alert Apply for this job * indicates a required field Autofill with MyGreenhouse First Name * Last Name * Preferred First Name Email * Phone Country * Phone * Location (City) * Locate me Resume/CV * Attach Attach Dropbox Google Drive Enter manually Enter manually Accepted file types: pdf, doc, docx, txt, rtf Education School * Select... Degree * Select... Discipline * Select... Start date year End date year Add another LinkedIn Profile Link * Please provide the URL to your LinkedIn; if you don't have one, please write "none". Github Link * Please provide the URL to your Github; if you don't have one, please write "none". Personal Website About You * Please provide the URL to your personal website, Google Scholar, etc if you have one. Put "none" if you do not. Current Company * Please tell us the name of your current employer (today if you are employed). Put "none" if this does not apply to you; for example, if you are in school or not currently employed -- this does not disqualify you. Feel free to enter previous roles in the field below in "Past Company 1". Current Title or Role * Please enter your current title at your current employer. If you are not currently employed (or in school etc) please enter "none" and feel free to enter previous roles in the field below in "Past Company". Past Company 1 * Please enter the Company name of your most recent previous employer. If you have not worked at another company before your current one, please enter “none”. Past Company Title or Role * Please enter your title at your most recent previous employer. If you have not worked at another company before your current one, please enter “none”. Past Company 2 If you would like, please enter the Company name of your second previous employer. If you have not worked at another company before your current or previous one, please enter “none” or skip this question. Past Company Title or Role 2 If you would like, please enter the Title or Job of your second previous employer. If you have not worked at another company before your current or previous one, please enter “none” or skip this question. What domains of research infrastructure do you have expertise in? * Numerics Kernels RL Infra Pre-training Infra Post-training Infra Inference Distributed Training Training frameworks (PyTorch, Jax, etc) ML Compilers ML Runtime Infra Other Select all that apply where you have actively completed work in and would be able to interview for in a technical interview. This will help us when picking between teams or projects! If you selected other, what areas did we not include that you have expertise in? * If you completed research under an advisor, such as through a PhD program or masters program where you published, who was your advisor? First name and last name of your Advisor / what program this was Do you have any links to publications we should read? Links to any publications, please list here List 3 projects you're proud of. Please list 3 projects you're proud of, using 1 sentence each. Feel free to add a link if helpful. Will you now or in the future require sponsorship for employment visa status in the United States? * Select... Voluntary Self-Identification For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file. As set forth in Thinking Machines Lab’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law. Gender Select... Are you Hispanic/Latino? Select... Race & Ethnicity Definitions If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection. As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measure the effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categories is as follows: A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to
compensation (or who but for the receipt of military retired pay would be entitled to
compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability. A "recently separated veteran" means any veteran during the three-year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service. An "active duty wartime or campaign badge veteran" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense. An "Armed forces service medal veteran" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985. Veteran Status Select... Voluntary Self-Identification of Disability Form CC-305 Page 1 of 1 OMB Control Number 1250-0005 Expires 04/30/2026 Why are you being asked to complete this form? We are a federal contractor or subcontractor. The law requires us to provide equal employment opportunity to qualified people with disabilities. We have a goal of having at least 7% of our workers as people with disabilities. The law says we must measure our progress towards this goal. To do this, we must ask applicants and employees if they have a disability or have ever had one. People can become disabled, so we need to ask this question at least every five years. Completing this form is voluntary, and we hope that you will choose to do so. Your answer is confidential. No one who makes hiring decisions will see it. Your decision to complete the form and your answer will not harm you in any way. If you want to learn more about the law or this form, visit the U.S. Department of Labor’s Office of Federal Contract Compliance Programs (OFCCP) website at www.dol.gov/ofccp . How do you know if you have a disability? A disability is a condition that substantially limits one or more of your “major life activities.” If you have or have ever had such a condition, you are a person with a disability. Disabilities include, but are not limited to: Alcohol or other substance use disorder (not currently using drugs illegally) Autoimmune disorder, for example, lupus, fibromyalgia, rheumatoid arthritis, HIV/AIDS Blind or low vision Cancer (past or present) Cardiovascular or heart disease Celiac disease Cerebral palsy Deaf or serious difficulty hearing Diabetes Disfigurement, for example, disfigurement caused by burns, wounds, accidents, or congenital disorders Epilepsy or other seizure disorder Gastrointestinal disorders, for example, Crohn's Disease, irritable bowel syndrome Intellectual or developmental disability Mental health conditions, for example, depression, bipolar disorder, anxiety disorder, schizophrenia, PTSD Missing limbs or partially missing limbs Mobility impairment, benefiting from the use of a wheelchair, scooter, walker, leg brace(s) and/or other supports Nervous system condition, for example, migraine headaches, Parkinson’s disease, multiple sclerosis (MS) Neurodivergence, for example, attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, dyslexia, dyspraxia, other learning disabilities Partial or complete paralysis (any cause) Pulmonary or respiratory conditions, for example, tuberculosis, asthma, emphysema Short stature (dwarfism) Traumatic brain injury Disability Status Select... PUBLIC BURDEN STATEMENT: According to the Paperwork Reduction Act of 1995 no persons are required to respond to a collection of information unless such collection displays a valid OMB control number. This survey should take about 5 minutes to complete. Submit application Powered by Greenhouse
