Research Intern, Frontier Speculative Decoding (Summer 2027)

About the Role

Together AI is building the Inference Platform that powers the world's most advanced generative AI models. Our team works on the critical bridge between cutting-edge research and real-world applications, focusing on translating our internal model training research to production-ready deployment for our customers. This involves a deep commitment to data-centric development, meticulous hyperparameter tuning, and rigorous checkpoint evaluation before models ever hit production. This role will involve understanding customer specific needs and fine-tuning models on our internal data recipe and their proprietary data. The goal is to transform general-purpose models into highly performant, specialized tools that solve real business problems. You will not be training foundation models from scratch but rather focusing on creating highly efficient, specialized models by working with dedicated GPU clusters. Responsibilities

Research and prototype new speculator algorithms, experimenting with architectural ideas and data curation to improve accuracy–efficiency tradeoffs in speculative decoding. Own a well-scoped project end to end, from data preparation through training and evaluation, with a real path to production. Learn how frontier inference systems work in practice, in a fast-paced environment at the cutting edge of generative AI. You'll collaborate directly with customers to understand their needs, and work closely with our core inference and Applied ML research teams to integrate your work into the production platform. Present your results to the broader team at the end of your internship, with the chance to influence the direction of our speculator work. A culture of deep technical ownership where you are empowered to take on and solve challenging problems Requirements

Currently pursuing a degree in Computer Science, Electrical Engineering, Information Science, or a related field A genuine love for data curation and processing, with a meticulous attention to detail. You believe that great models start with great data. Demonstrated ability to perform effective hyperparameter searches and understand the trade-offs involved in tuning models for specific tasks. Strong attention-to-detail in evaluating model checkpoints to ensure they meet strict quality, performance, and reliability standards. Experience with Python and PyTorch. Familiarity with SLURM and/or Kubernetes clusters and experience submitting and managing jobs in a high-performance computing environment. Familiarity with modern LLMs and generative models. Basic understanding of distributed training frameworks (e.g., FSDP, DeepSpeed). Publications at leading research conferences or journals (such as NeurIPS, ICML, ICLR, *ACL, EMNLP, Interspeech) 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. Internship Program Details

Our internship program runs 12 to 14 weeks, giving you the opportunity to work alongside industry-leading engineers and researchers across multiple teams. This cohort's internship dates span May 17th to August 6th or June 14th to September 3rd. Compensation

We offer competitive compensation, housing stipends, and other competitive benefits. The estimated US hourly rate for this role is $58 - $70 an hour. 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. For more information about our privacy policy, please visit: