Jobs at Together AI

Operate and scale multi-petabyte distributed storage for AI and HPC workloads. Design high-performance parallel filesystems, object stores, caching architectures, and Kubernetes-native storage operators. Optimize data paths, throughput, multi-tenancy, cost, and reliability across thousands of GPU nodes. Integrate technologies such as Vast, Weka, Ceph, and Lustre; develop automation and tooling in Go and Python; and contribute to storage infrastructure, observability, benchmarking, and open-source projects.

Build production software for automated GPU and inference cluster provisioning. Design declarative APIs, control planes, state machines, reconciliation loops, durable workflows, and self-healing systems that manage hardware from discovery through deployment, operation, repair, and decommissioning. Partner with inference and ML platform teams to model cluster topology and scheduling requirements. Own reliability, testing, CI/CD, deployment, and production operations for the platform.

Operate and scale Together AI's production infrastructure: run GPU-enabled Kubernetes clusters, automate with Ansible and Terraform, build monitoring/observability, respond to incidents (on-call), debug production issues, design deployment/upgrade processes, and plan infrastructure growth for high availability and scalability.

Leads Together AI’s partner marketing function by defining strategy, messaging, and co-marketing execution with NVIDIA and cloud partners. Collaborates with GTM, product marketing, demand generation, and field marketing teams to deliver campaigns, establish partner operating rhythms, track performance metrics, and improve ROI. The role requires building the function from the ground up and scaling partner go-to-market programs for a B2B AI or software platform business.

Lead platform infrastructure strategy and build reusable service infrastructure across Kubernetes, AWS, networking, and operational systems. Develop Helm charts, Terraform modules, CI/CD, GitOps workflows, zero-trust policies, and self-service platform capabilities. Partner with service, SRE, security, networking, and infrastructure teams to modernize services and drive adoption of shared patterns. Lead cross-company infrastructure initiatives and establish an initial platform infrastructure team.

Coordinates recruiting activities from interview scheduling through offers, background checks, onboarding transitions, and candidate communication. Maintains ATS records, prepares recruiting metrics, supports hiring managers and interviewers, improves recruiting processes, and ensures a positive candidate experience. Requires strong organization, communication, adaptability, confidentiality, and familiarity with recruiting tools and office productivity software.

Own full-cycle recruiting for go-to-market and business teams in a high-growth AI company. Partner with executives to define hiring strategies, candidate profiles, and interview processes; manage candidates through offer close; provide market intelligence and funnel metrics; and improve recruiting workflows and candidate experience. The role requires strategic leadership partnership, adaptability in ambiguity, and experience building recruiting processes from the ground up.

Lead architecture and implementation of Together AI’s global GPU cloud infrastructure. Own GPU and network virtualization, in-data-center IaaS, distributed scheduling and management planes, fault-tolerant automation, and customer-facing production systems. Set technical direction across teams, mentor engineers, establish engineering standards, and build scalable services spanning Kubernetes, compute, storage, networking, and GPU infrastructure.

Conduct research on frontier AI agents, including alignment, reliability, long-horizon reasoning, dataset design, evaluation, safety, and scalable infrastructure. Develop novel techniques, run rigorous experiments, document findings in publications and blog posts, and communicate project progress. Work may involve machine learning, deep learning, reinforcement learning, spoken-input agents, and foundation model development.

Software Engineer Interns will design, develop, and maintain software across platform, infrastructure, inference, and product engineering teams. Responsibilities include building features, writing maintainable code, collaborating cross-functionally, participating in code reviews, debugging, and optimizing performance. The 12-week, on-site internship is based at the company headquarters in San Francisco and may involve cloud infrastructure and open-source projects.

Develop and optimize GPU-accelerated kernels and algorithms for AI and machine learning applications. Collaborate with modeling, algorithm, hardware, and software teams on GPU architecture and programming-model co-design. Integrate GPU solutions into software systems, optimize performance and scalability, and track advances in GPU programming techniques. The internship lasts 12–14 weeks and includes cross-functional research and engineering work.

Conduct frontier AI research focused on agentic systems, alignment, reliability, evaluation, datasets, self-learning, and long-horizon reasoning. Responsibilities include implementing novel techniques, designing rigorous experiments, documenting findings in publications and blog posts, and communicating project results. Work may involve training and evaluating models, developing safety paradigms, building spoken-input agents, and creating scalable ML infrastructure.

Develop automated tests for website and service functionality, performance, and reliability. Improve test automation frameworks, expand coverage, write maintainable code, and collaborate with engineering and product teams on test plans and quality standards. The intern will gain exposure to AI infrastructure, model benchmarking, API testing, and CI automation.

Develop and optimize GPU-accelerated kernels and algorithms for ML/AI applications. Collaborate with modeling, algorithm, hardware, and software teams on GPU and programming-model co-design, integrate optimized solutions, and apply performance profiling techniques to improve scalability and efficiency.

Software Engineer Interns will design, develop, and maintain software across platform engineering, infrastructure, SRE, and inference teams. Responsibilities include building product features, writing maintainable code, collaborating cross-functionally, participating in code reviews, debugging, and optimizing performance. Interns will contribute to projects from initial scope through production and may work on cloud infrastructure or open source initiatives.

Conduct research on efficient, scalable inference systems for foundation models. Design experiments, develop cross-layer optimizations across models, software, and hardware, and investigate distributed inference, speculative decoding, KV cache design, compiler optimization, and large-scale serving. Communicate project progress and results, and document findings in scientific publications and blog posts.

Conduct research on efficient, scalable inference systems for foundation models. Design experiments, develop cross-layer optimizations across models, software, and hardware, and investigate distributed inference, speculative decoding, KV cache design, and serving architectures. Communicate project results and document findings through scientific publications and blog posts.

Early-career software engineer designing, developing, and maintaining software across systems, infrastructure, machine learning, inference, and user-facing products. Responsibilities include collaborating cross-functionally, owning projects, participating in code reviews, debugging, optimizing performance, and contributing to technical direction. Candidates should have strong computer science fundamentals, hands-on development experience, Git proficiency, creative problem-solving ability, and effective communication skills.

Lead Together AI’s technical community engagement strategy across X, LinkedIn, and Discord. Own content strategy, grow developer and researcher engagement, collaborate with marketing, developer relations, and solutions teams, and experiment with new content formats, competitions, and community initiatives. The role is primarily online, with some responsibility for in-person meetups and events. It requires developer marketing and community engagement experience, strong knowledge of AI developers, social media fluency, ownership, and data-driven experimentation.

Own and build Together AI’s brand marketing function by developing the brand narrative, campaigns, messaging, visual identity, channel execution, and measurement strategy. Lead internal and vendor design resources, manage brand budgets, guide thought leadership, track awareness and sentiment, and foster experimentation to scale high-performing brand initiatives.