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Systems Research Engineer, GPU Programming

Together AI · Not provided by source

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Last seen by MeritLog September 9, 2026Source: GreenhouseSource version: greenhouse-job-board-v1

Source: the employer's Greenhouse job board. Open the original listing for current details. Availability is not verified for this retained page.

Job details

Work model: Not provided by source
Salary: Conflicting source ranges
Location: San Francisco

What the role asks for

What you'd do

Optimize and fine-tune GPU code to achieve better performance and scalability
Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems
Stay up-to-date with the latest advancements in GPU programming techniques and technologies

What they're asking for

Strong background in GPU programming and parallel computing, such as CUDA and/or Triton.Skill
Knowledge of ML/AI applications and modelsSkill
Knowledge of performance profiling and optimization tools for GPU programmingSkill
Excellent problem-solving and analytical skillsSkill
Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or equivalent practical experiencesEducation

Parsed by MeritLog from the employer’s own posting. The full description follows below.

Job description

About the Role As a Systems Research Engineer specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and programming models, leveraging your expertise in GPU programming and parallel computing. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation. Requirements • Strong background in GPU programming and parallel computing, such as CUDA and/or Triton. • Knowledge of ML/AI applications and models • Knowledge of performance profiling and optimization tools for GPU programming • Excellent problem-solving and analytical skills • Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or equivalent practical experiences Responsibilities • Optimize and fine-tune GPU code to achieve better performance and scalability • Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems • Stay up-to-date with the latest advancements in GPU programming techniques and technologies About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Compensation We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $200,000 - $300,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at https://www.together.ai/privacy

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