{"schemaVersion":"jobsearcher.job.v1","id":"17c9949ec13c58a2bb556513","url":"https://jobsearcher.com/jobs/17c9949ec13c58a2bb556513","canonicalUrl":"https://jobsearcher.com/jobs/17c9949ec13c58a2bb556513","title":"Research Engineer, Post-Training Inference","description":"About the role\nThe Model Shaping team at Together AI works on products and research focused on tailoring open foundation models to downstream applications. We build services that enable machine learning developers to choose the best models for their tasks and further improve these models using domain‑specific data. In addition, we develop new methods for more efficient model training and evaluation, drawing inspiration from a broad range of ideas across machine learning, natural language processing, and ML systems.\n\nAs a Research Engineer within Model Shaping, you will develop a platform that enables users to customize open‑source models with their own data. Working across the training and inference stacks, you will build and improve our Fine‑Tuning, Reinforcement Learning, and Evaluation services – from ensuring a seamless path from post‑training to production serving, to optimizing the inference engine for RL training workloads. You will collaborate closely with our product, research, and engineering teams to keep the API reliable, performant, and well integrated into the company's technical infrastructure. Above all, you will help build the foundational layer of the open‑source AI ecosystem, enabling developers around the world to efficiently create high‑quality models tailored to their specific applications.\n\nResponsibilities\n\nDesign and build Together’s systems for customizing open‑source models\n\nBuild integrations between the Model Shaping and Inference platforms to ensure a seamless path from post‑training to serving production workloads\n\nAdd features to inference engines for large‑scale post‑training experiments, including optimizations for RL workloads\n\nMake sure the service is stable and robust, participating in an on‑call rotation and ensuring 24/7 availability of our platform\n\nRequirements\n\nHave 2+ years of experience building and deploying machine learning‑based services in a production environment\n\nHave hands‑on experience with modern inference engines, such as SGLang, vLLM, and TensorRT‑LLM\n\nAre familiar with the latest methods for fine‑tuning LLMs and other AI models\n\nHave a strong software engineering background in Python or Go\n\nStay up to date with the latest advances and trends in the machine learning community\n\nExperience in any of the following will make you stand out\n\nServing low‑precision (FP4/FP8) models, multiple LoRA adapters within one model instance (Multi‑LoRA), or models distributed across several GPU nodes\n\nOptimizing the performance of RL training workloads\n\nDeveloping CUDA/Triton/CuTE DSL kernels for inference\n\nDeveloping large‑scale and high‑load production systems\n\nMaintaining or contributing to open‑source ML projects\n\nManaging machine learning workloads on Kubernetes clusters\n\nAbout Together AI\nTogether 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, hardware, 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 advancement such as FlashAttention, ATLAS, RedPajama, and Mamba. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.\n\nCompensation\nWe offer competitive compensation, startup equity, health insurance, and other benefits. The US base salary range for this full‑time position is $200,000 - $290,000. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job‑related knowledge.\n\nEqual Opportunity\nTogether 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.\n\nPlease see our privacy policy at https://www.together.ai/privacy\n\n#J-18808-Ljbffr","company":"Togetherai","rawCompany":"togetherai","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-07-16T03:22:22.080Z","occupations":[{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Research Engineer, Post-Training Inference","description":"About the role\nThe Model Shaping team at Together AI works on products and research focused on tailoring open foundation models to downstream applications. We build services that enable machine learning developers to choose the best models for their tasks and further improve these models using domain‑specific data. In addition, we develop new methods for more efficient model training and evaluation, drawing inspiration from a broad range of ideas across machine learning, natural language processing, and ML systems.\n\nAs a Research Engineer within Model Shaping, you will develop a platform that enables users to customize open‑source models with their own data. Working across the training and inference stacks, you will build and improve our Fine‑Tuning, Reinforcement Learning, and Evaluation services – from ensuring a seamless path from post‑training to production serving, to optimizing the inference engine for RL training workloads. You will collaborate closely with our product, research, and engineering teams to keep the API reliable, performant, and well integrated into the company's technical infrastructure. Above all, you will help build the foundational layer of the open‑source AI ecosystem, enabling developers around the world to efficiently create high‑quality models tailored to their specific applications.\n\nResponsibilities\n\nDesign and build Together’s systems for customizing open‑source models\n\nBuild integrations between the Model Shaping and Inference platforms to ensure a seamless path from post‑training to serving production workloads\n\nAdd features to inference engines for large‑scale post‑training experiments, including optimizations for RL workloads\n\nMake sure the service is stable and robust, participating in an on‑call rotation and ensuring 24/7 availability of our platform\n\nRequirements\n\nHave 2+ years of experience building and deploying machine learning‑based services in a production environment\n\nHave hands‑on experience with modern inference engines, such as SGLang, vLLM, and TensorRT‑LLM\n\nAre familiar with the latest methods for fine‑tuning LLMs and other AI models\n\nHave a strong software engineering background in Python or Go\n\nStay up to date with the latest advances and trends in the machine learning community\n\nExperience in any of the following will make you stand out\n\nServing low‑precision (FP4/FP8) models, multiple LoRA adapters within one model instance (Multi‑LoRA), or models distributed across several GPU nodes\n\nOptimizing the performance of RL training workloads\n\nDeveloping CUDA/Triton/CuTE DSL kernels for inference\n\nDeveloping large‑scale and high‑load production systems\n\nMaintaining or contributing to open‑source ML projects\n\nManaging machine learning workloads on Kubernetes clusters\n\nAbout Together AI\nTogether 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, hardware, 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 advancement such as FlashAttention, ATLAS, RedPajama, and Mamba. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.\n\nCompensation\nWe offer competitive compensation, startup equity, health insurance, and other benefits. The US base salary range for this full‑time position is $200,000 - $290,000. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job‑related knowledge.\n\nEqual Opportunity\nTogether 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.\n\nPlease see our privacy policy at https://www.together.ai/privacy\n\n#J-18808-Ljbffr","datePosted":"2026-07-16T03:22:22.080Z","dateModified":"2026-07-16T03:22:22.080Z","hiringOrganization":{"@type":"Organization","name":"Togetherai","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"17c9949ec13c58a2bb556513"},"url":"https://jobsearcher.com/jobs/17c9949ec13c58a2bb556513"}}