Strategic Overview
Member of Technical Staff (GPU Performance Engineer) at Reka is a dev opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.
The published role emphasizes work such as Experience scaling up GPU jobs using large-scale compute clusters (e.g., Slurm or Kubernetes). An Elite Team: Collaborate with top-tier engineers, researchers, and operators from renowned organizations like Google DeepMind, Facebook AI Research (FAIR), and…
The role is listed for Singapore, United Kingdom, United States with remote working arrangement, giving candidates the practical context needed to assess fit before applying. Relevant signals in the listing include Software Engineering, Senior.
Key information at a glance
About This Role
We are seeking an experienced GPU Performance Engineer with a strong background in Python and large-scale model training. In this role, you will design and implement improvements to our training infrastructure and directly contribute to technical decisions that optimize performance of our models. You will also work on post-training processes, including reinforcement learning and fine-tuning. Furthermore, you will…
Ideal Experience
Reka's Mission Reka's mission is to build useful multimodal artificial intelligence and use it to empower organizations and businesses. We are a globally distributed foundation model startup, headquartered in the San Francisco Bay Area, California. Embracing a remote-first approach, our team brings together top talent from around the world. Our founding team, along with many of our team members, has contributed to…
Key Responsibilities & Objectives
- Experience scaling up GPU jobs using large-scale compute clusters (e.g., Slurm or Kubernetes).
- An Elite Team: Collaborate with top-tier engineers, researchers, and operators from renowned organizations like Google DeepMind, Facebook AI Research (FAIR), and successful startups, driving innovation in AI technology.
- Generous Benefits: Enjoy five weeks of paid leave to recharge, comprehensive healthcare benefits (including vision and dental), and additional perks that support your well-being.
- Visa Support: We provide visa assistance, including H1B and OPT transfers, for US employees to ensure a smooth transition and support your career with us.
Required Qualifications & Candidate Blueprint
- Strong engineering skills with fluency in Python and PyTorch (or other frameworks).
- Demonstrated ability to analyze and optimize the performance of GPU-accelerated workloads, including profiling, identifying bottlenecks, and implementing performance tuning techniques.
Salary & Benefits
The available source data does not publish a numerical salary range for this opening. We do not estimate or substitute third-party figures.
- Generous Benefits: Enjoy five weeks of paid leave to recharge, comprehensive healthcare benefits (including vision and dental), and additional perks that support your well-being.
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
We are seeking an experienced GPU Performance Engineer with a strong background in Python and large-scale model training. In this role, you will design and implement improvements to our training infrastructure and directly contribute to technical decisions that optimize performance of our models. You will also work on post-training processes, including reinforcement learning and fine-tuning. Furthermore, you will contribute to improving the efficiency and scalability of our model serving infrastructure.
Ideal Experience
Strong engineering skills with fluency in Python and PyTorch (or other frameworks).
Proven experience implementing and training large deep learning models.
Experience writing and debugging low-level GPU code (CUDA, C++).
Experience scaling up GPU jobs using large-scale compute clusters (e.g., Slurm or Kubernetes).
Demonstrated ability to analyze and optimize the performance of GPU-accelerated workloads, including profiling, identifying bottlenecks, and implementing performance tuning techniques.
Reka's Mission
Reka's mission is to build useful multimodal artificial intelligence and use it to empower organizations and businesses. We are a globally distributed foundation model startup, headquartered in the San Francisco Bay Area, California. Embracing a remote-first approach, our team brings together top talent from around the world. Our founding team, along with many of our team members, has contributed to numerous breakthroughs in AI over the past decade.
Why Reka?
An Elite Team: Collaborate with top-tier engineers, researchers, and operators from renowned organizations like Google DeepMind, Facebook AI Research (FAIR), and successful startups, driving innovation in AI technology.
Cutting-edge Infrastructure: Train state-of-the-art models leveraging the latest software and hardware, expanding the frontier of innovation in AI infrastructure development.
Inclusive and Open Culture: Thrive in an open and inclusive work environment that values diverse perspectives and fosters creativity.
Generous Benefits: Enjoy five weeks of paid leave to recharge, comprehensive healthcare benefits (including vision and dental), and additional perks that support your well-being.
Visa Support: We provide visa assistance, including H1B and OPT transfers, for US employees to ensure a smooth transition and support your career with us.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This dev opening is a useful opportunity for candidates whose experience matches Software Engineering, Senior. Its strongest career signal is the scope of the work itself — particularly Experience scaling up GPU jobs using large-scale compute clusters (e.g., Slurm or Kubernetes). — rather than a generic title alone.
Resume & Application Strategy
For the application, mirror the employer's language where it truthfully matches your background: foreground Software Engineering, Senior, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.
We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.