As a Research Engineer, you'll connect research with production, focusing on optimizing generative AI models and collaborating on customer-specific needs.

Lead the Sandbox team at Together AI, managing engineers and overseeing technical direction, project management, and team growth while ensuring sandbox infrastructure develops efficiently for AI execution.

The Solutions Architect will act as a technical advisor, collaborate on AI solutions, run demonstrations, and ensure customer success by integrating technical solutions with business needs.

Lead the design of AI developer tools: own end-to-end product UX, evolve and maintain a production design system, conduct user research, prototype and ship features, and partner with engineering and product to ensure high implementation quality and cross-product consistency.

The Customer Support Engineer will resolve technical challenges for customers involving AI solutions, collaborating with internal teams to improve offerings and ensure customer satisfaction.

Lead technical ownership and evolution of the product runtime and application architecture. Improve performance, reliability, observability, CI/CD, and runtime patterns for a Next.js-based web stack. Drive separation of API responsibilities, mentor engineers, and implement scalable, production-ready platform improvements to support rapid, reliable product development.

As a Product Marketing Intern, you will manage product launch activities, draft marketing content, analyze product adoption, and support cross-functional teams to enhance market execution for AI products.

The Senior Counsel, Commercial will negotiate and manage commercial agreements, provide legal advice to stakeholders, and develop contract processes, aiming to support business growth at Together AI.

The Senior Backend Engineer will develop scalable backend services for an AI cloud platform, enhance existing systems, and partner with product teams, ensuring robust and efficient cloud services.

As an AI Researcher, you will develop novel architectures and optimizations in machine learning, collaborating with teams to enhance open models and ensuring cutting-edge research practices.

Design and build production systems for AI inference, optimize runtime services, and collaborate on AI solutions with researchers and engineers.

Develop systems and APIs for LLM inference and fine-tuning. Design production systems, collaborate with teams, and improve system efficiency.

The Senior Data Engineer will build and operate data infrastructure for high-volume event processing, enhance scalability, and collaborate with product teams on analytics systems.

The role involves designing and optimizing distributed inference engines for multimodal LLMs, ensuring high performance and cost efficiency.

The role involves developing and optimizing GPU-accelerated kernels for ML/AI applications, collaborating with teams to enhance AI systems' performance.

Lead end-to-end strategic sourcing for GPUs, servers, networking, and storage; negotiate multi-million-dollar supply agreements; design inventory, logistics, and supplier strategies; build procurement tools and present supply-chain risks and recommendations to executive leadership.

The role entails optimizing model performance and developer experience through serverless inference platforms, distributed systems, and API development. Responsibilities include enhancing system robustness and scalability, partnering with product teams, and maintaining clean software and IaC.

Translate RL and inference research into production systems to improve latency, throughput, cost, and model quality. Design and implement inference engines and scheduling, build RL/post‑training pipelines, profile and optimize GPU/network/memory performance, run scale experiments, and drive production roadmap and benchmarks. Provide technical leadership and mentor others.

The Senior Backend Engineer will optimize and build systems for the Inference Platform, focusing on low-latency, scalability, and performance for generative AI models. Responsibilities include enhancing request routing, developing auto-scaling systems, and collaborating with ML researchers to implement new model architectures in production.

Develop and maintain a global AI cloud infrastructure, focusing on high-performance backend services, IaaS software, and robust observability solutions.