Research Intern, Inference (Fall 2026)
Together AI
Research Intern, Inference (Fall 2026) at Together AI is a full time role based in San Francisco, California, United States. It was published on 12 June 2026 and was open at last check.
| Role | Research Intern, Inference (Fall 2026) |
|---|---|
| Company | Together AI |
| Location | San Francisco, California, United States |
| Employment type | Full Time |
| Published | 12 June 2026 |
| Status | Open at last check |
About The Role
The Inference Research team is dedicated to building the next generation of efficient, scalable, and reliable serving systems for large foundation models, directly contributing to the mission of advancing open and transparent AI. Our work operates at the critical intersection of cutting-edge model architectures, high-performance systems engineering, and deep hardware optimization. We focus on co-designing software, algorithms, and models to significantly lower the cost and latency of modern AI systems.
As a research intern, you will dive into the complexities of distributed inference, compiler-aware optimization, and novel inference-time computation strategies (such as speculative decoding and phase-aware execution). You will be tasked with co-designing and implementing cross-layer optimizations across models, systems, and hardware, with a focus on areas like KV cache design and large-scale serving architectures.
Projects aim to unlock unprecedented performance and scale for foundation models, enabling faster serving, larger model deployment (e.g., Mixture-of-Experts), and robust, reproducible evaluation under realistic serving workloads.
Responsibilities
- Design and conduct rigorous experiments to validate hypotheses
- Communicate the plans, progress, and results of projects to the broader team
- Document findings in scientific publications and blog posts
Requirements
- Currently pursuing a final year of Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or a related field
- Strong knowledge of Machine Learning and Deep Learning fundamentals
- Experience with deep learning frameworks (PyTorch, JAX, etc.)
- Strong programming skills in Python
- Familiarity with Transformer architectures and recent developments in foundation models
Preferred Qualifications
- Prior research experience in foundation models, efficient machine learning, or ML systems.
- Publications at leading conferences in machine learning or systems (i.e., MLSys, ICLR).
- Experience with CUDA programming (for kernel development)
- Understanding of model optimization techniques and hardware acceleration approaches
- Contributions to open-source machine learning projects
Internship Program Details
Our fall internship program spans over 12 to 16 weeks where you’ll have the opportunity to work with industry-leading engineers building a cloud from the ground up and possibly contribute to influential open source projects. Our internship dates are September 14th to December 18th.
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, 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 advancements such as FlashAttention, Mamba, FlexGen, Petals, Mixture of Agents, and RedPajama.
Compensation
We offer competitive compensation, housing stipends, and other competitive benefits. The estimated US hourly rate for this role is $58-63/hr. Our hourly rates 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
Create your free OnJob profile to apply — we'll take you to Together AI's application after sign-up. · Posted 12 Jun 2026.
Research Intern, Inference (Fall 2026) at Together AI — questions answered
What does the Research Intern, Inference (Fall 2026) role at Together AI pay?
Together AI does not publish a salary on this Research Intern, Inference (Fall 2026) listing, so OnJob shows no figure for it rather than an estimate. For what this role pays across the market, the OnJob salary guides aggregate the live listings that do disclose pay.
Where is the Research Intern, Inference (Fall 2026) role at Together AI based?
Together AI lists this Research Intern, Inference (Fall 2026) role in San Francisco, California, United States, advertised as full time work at that location. Larger employers sometimes cover several sites under one city name, so confirm the exact office with Together AI before you apply.
Is the Research Intern, Inference (Fall 2026) role at Together AI still open?
The Research Intern, Inference (Fall 2026) posting at Together AI was open at OnJob's last check of the employer's careers page, having been published on 12 June 2026. OnJob re-checks source listings on each build and marks a role closed once it disappears, but listings can close without notice, so the employer's own page is the final word.
How do you apply for the Research Intern, Inference (Fall 2026) role at Together AI?
Apply to the Research Intern, Inference (Fall 2026) at Together AI role through OnJob with a free profile: OnJob scores your fit against the listing, shows the skills lowering that score, and submits an ATS-ready profile to Together AI's own application page. Creating a profile is free and needs no card.
Related jobs you can win
Hand-picked roles that match this listing on skills, category and location — each scored to your profile inside OnJob.
Explore more on OnJob
Hiring for a role like this?
Post a job on OnJob and reach AI-matched candidates.