Member of Technical Staff, Research (2026 PhD New Grad)
Company websitefireworks.ai (Fireworks AI, opens in new tab)
Base salary $200K to $300K
Employer-published annual base salary, USD. Advertised base range in San Mateo, CA +1 more
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSan Mateo, CA +1 more
- WorkplaceHybrid
- Status at last checkSource accepting applications when checked
- Last checked (1 h ago) · observed since
All places named
- San Mateo, CA
- New York, NY
About this job
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
Conduct foundational research to advance the capabilities, efficiency, and reliability of LLMs and multimodal systems
Design, implement, and evaluate novel model architectures, training methods, and optimization techniques
Work alongside engineering teams to transition research prototypes into production-grade systems
Analyze empirical results, identify performance bottlenecks, and iterate quickly to improve model quality
Bring ideas and emerging directions from your doctoral research into our internal research agenda
MINIMUM QUALIFICATIONS:
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
Research background in Artificial Intelligence, Machine Learning, Physics, or a related area, demonstrated through your dissertation, publications, or research projects
Experience solving analytical problems using analytic and quantitative approaches
Experience communicating research to audiences with different backgrounds
Proficiency coding in Python, C/C++, or other similar languages
Hands-on experience with ML frameworks such as PyTorch, JAX, or TensorFlow
PREFERRED QUALIFICATIONS:
First-authored publications at top-tier peer-reviewed conferences or journals (NeurIPS, ICML, ICLR, MLSys, or similar)
Industry research internships, or open-source contributions to ML systems, model training, or inference projects
Research or engineering experience demonstrated via grants, fellowships, patents, or coding competitions
Experience with large-scale model training, distributed systems, GPU kernel development, or inference optimization
Experience taking research code beyond the prototype stage
Why Fireworks?
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Source: Fireworks AI on Ashby · View original posting (opens in new tab)
This listingMember of Technical Staff, Research (2026 PhD New Grad)$200K to $300K
Member of Technical Staff, Systems Infrastructure (2026 PhD New Grad)$200K to $230K
Senior GRC Specialist$200K to $220K
Member of Technical Staff, AI Infrastructure Reliability$200K to $290K
Member of Technical Staff, Nexus$200K to $290K
Member of Technical Staff, Software Engineer$200K to $290K
Product Manager$200K to $300K
Chart as a table
| Role | Published base |
|---|---|
| Member of Technical Staff, Research (2026 PhD New Grad) (this listing) | $200K - $300K |
| Member of Technical Staff, Systems Infrastructure (2026 PhD New Grad) | $200K - $230K |
| Senior GRC Specialist | $200K - $220K |
| Member of Technical Staff, AI Infrastructure Reliability | $200K - $290K |
| Member of Technical Staff, Nexus | $200K - $290K |
| Member of Technical Staff, Software Engineer | $200K - $290K |
| Product Manager | $200K - $300K |
Observed changes
- Began meeting the published-salary criteria
- First observed on the employer's board
- Observed since
- Employer-stated posting date
- 2026-09-08
Where this pay comes from
Location as the employer wrote it: San Mateo • New York
USD 200,000 – 300,000 · 1 YEAR · Salary
- Method
- Structured pay field published by the employer
- Checked
- Rule set
- us-base-v2
The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
