Member Of Technical Staff
US$200,000 – US$300,000 / yr base salary
Posted 8 Sep 2026
Advertised as “Member of Technical Staff, Research (2026 PhD New Grad)”
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- Hybrid
- Contract
- Full-time
| Base salary | US$200,000 – US$300,000 / yr |
|---|
Field of studyComputer Science, Electrical Engineering, Machine learning, Mathematics, Physics (or related)
Study levelDoctorate
About Us:
Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI.
THE ROLE:
This role is designed for researchers finishing their PhD who want their work to reach production, not just publication. As a Member of Technical Staff on the Research team, you'll push the boundaries of generative AI, advancing LLMs and multimodal systems through foundational research. Your work will enhance model efficiency, accuracy, and scalability, directly shaping our high-performance AI infrastructure.
You'll be paired with a senior researcher as a mentor and given a real research problem from day one. You'll collaborate with top experts in deep learning, distributed systems, and optimization, and you'll see the models you help create deployed by some of the world's leading companies — often within weeks rather than years.
We welcome candidates who have completed within the last 6 months, or expected completion by December 2026.
KEY RESPONSIBILITIES
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Conduct foundational research to advance the capabilities, efficiency, and reliability of LLMs and multimodal systems
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Design, implement, and evaluate novel model architectures, training methods, and optimization techniques
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Work alongside engineering teams to transition research prototypes into production-grade systems
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Analyze empirical results, identify performance bottlenecks, and iterate quickly to improve model quality
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Bring ideas and emerging directions from your doctoral research into our internal research agenda
MINIMUM QUALIFICATIONS:
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PhD completed within the last 6 months, or expected completion by December 2026, in Computer Science, Machine Learning, Computational Physics, Mathematics, Electrical Engineering, or a similar field
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Research background in Artificial Intelligence, Machine Learning, Physics, or a related area, demonstrated through your dissertation, publications, or research projects