Systems Research Engineer specialized in GPU Programming

Together Ai
San Francisco, CA, United States
15 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$160,000.0 - $230,000.0
Working hours
Regular working hours
Job source

Tech stack

Computer-Aided Design Artificial Intelligence Program Optimization Profiling Nvidia CUDA Systems Theories Open Source Technology Software Systems AI Infrastructure Parallel Computation Gpu Programming Information Technology

Job description

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., * 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 is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

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

Benefits & conditions

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: $160,000 - $230,000 + 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

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:30 min

Exploring the Python-enabled GPU programming software stack

Paul Graham Paul Graham · WWC Europe 2026

6:21 min

Previewing upcoming hardware acceleration capabilities for Python environments

Chris Heilmann +2 · LIVE

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Profiling native execution calls with async-profiler

Gonzalo Ortiz Jaureguizar Gonzalo Ortiz Jaureguizar · WWC Europe 2026

4:20 min

Utilizing AI and hardware acceleration for application code optimization

Stephan Gillich Stephan Gillich · WWC 2024

2:33 min

Architecting CUDA and the AI software stack

Michael Kagan Michael Kagan +1 · WWC Europe 2026

3:30 min

Transitioning from CUDA software architect to user

Stephen Jones · Coffee With Developers

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