Systems Research Engineer, GPU Programming

Togetherai; San Francisco (CA); Hybrid; USD 160,000 - 230,000; Full time

Benefits offered by this job

Competitive compensation

Startup equity

Health insurance

Remote work flexibility

Job summary

Togetherai, based in San Francisco, is seeking a Systems Research Engineer specialized in GPU Programming. The role focuses on optimizing GPU-accelerated kernels and collaborating with teams to enhance AI system performance.

Ideal candidates will possess a strong background in GPU programming, relevant degrees, and the ability to innovate in a fast-paced environment. This full-time position offers competitive compensation between $160,000 and $230,000, equity, health insurance, and benefits.

Qualifications

• Strong background in GPU programming and parallel computing.
• Knowledge of ML/AI applications and models.
• Knowledge of performance profiling and optimization tools.

Responsibilities

• Optimize and fine-tune GPU code for performance.
• Collaborate to integrate GPU solutions into software systems.
• Stay updated on advancements in GPU programming.

Skills

GPU programming

Parallel computing

CUDA/Triton

ML/AI knowledge

Performance profiling

Problem-solving skills

Analytical skills

Education

Bachelor's, Master's, or Ph.D. in Computer Science or Electrical Engineering

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 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.

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: $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

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.