Systems Research Engineer, GPU Programming
At a glance
Mid-level AI Research role at Together AI. San Francisco · $200,000–$300,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Tune GPU code so it runs faster and scales more effectively
- Work with modeling and algorithm colleagues to shape GPU kernels alongside model architecture
- Coordinate with hardware and software teams on efficient GPU designs and programming approaches
- Bring GPU-accelerated components into existing software, working across teams
- Track new GPU programming methods and technologies to guide ongoing work
What you bring
- You have a strong grounding in GPU programming and parallel computing, such as CUDA or Triton
- You understand machine-learning applications and models, plus GPU profiling and optimization tools
- You hold a computer science or electrical engineering degree, or have equivalent practical experience
Who this fits
This mid-level role suits someone focused on GPU programming for machine-learning systems, with strengths in parallel computing and performance tuning. The position is based in San Francisco, and the stated annual base salary range is $200,000 to $300,000, plus equity and benefits.
From the employer
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