Prime Intellect

Leads the recruiting function, personally owning senior frontier AI and infrastructure searches while building sourcing, interview, compensation, and recruiting operations systems. Requires 5+ years of technical recruiting experience and a strong network in AI research or advanced infrastructure.

Build and operate a hosted AI training platform spanning Kubernetes GPU orchestration, Python control-plane services, developer-facing APIs, and monitoring interfaces. The role requires depth across AI infrastructure, distributed training, cloud operations, and full-stack platform development.

Build distributed sandbox infrastructure and developer-facing AI workload platforms across systems, backend, and frontend layers. The role requires strong Rust and Linux systems expertise alongside Python backend and modern web development experience.

Build and optimize large-scale LLM inference and serving infrastructure across cloud GPU fleets, integrating inference systems with RL training. Requires 3+ years operating ML/LLM services, strong distributed systems and GPU expertise, and hands-on experience with modern inference frameworks.

Designs, deploys, and supports large-scale GPU and HPC infrastructure for customers, including cluster architecture, orchestration, networking, storage, and performance optimization. Requires 3+ years of GPU/HPC experience, production SLURM and Kubernetes expertise, and strong customer-facing technical leadership.

Build and operate the developer-facing web platform, APIs, and services used to train and deploy frontier AI models. The role requires strong Python and modern frontend experience, cloud and containerized deployment expertise, and end-to-end ownership of production features.

Build the full-stack compute platform for frontier AI workloads, spanning Python services, web interfaces, distributed Rust infrastructure, cloud orchestration, and heterogeneous hardware scheduling. The role requires strong backend, frontend, systems, and infrastructure experience.

Build and optimize infrastructure for frontier-scale reinforcement learning and distributed model training, including kernels, runtimes, parallelism, and asynchronous rollouts. The role requires strong AI/ML systems experience, PyTorch expertise, and GPU performance optimization skills.

Conducts frontier research and builds scalable synthetic-data and distributed reinforcement-learning infrastructure for large AI models. Requires strong AI/ML engineering experience, distributed inference expertise with tools such as vLLM or SGLang, and MLOps knowledge.

Research Engineer building and optimizing distributed infrastructure for frontier-scale model training and reinforcement learning. The role requires strong AI systems experience, PyTorch and distributed-training expertise, GPU performance optimization, and familiarity with parallelism and large-scale clusters.

Interns will build open, distributed AI systems and infrastructure across areas such as frontier AI, distributed computing, systems, and cryptography. The role is suited to exceptional builders with substantial project or open-source experience who learn quickly and execute well.

Leads marketing and developer relations for an open AI infrastructure platform, overseeing brand, content, community, launches, growth, and marketing operations. Requires 5+ years of relevant experience, strong technical fluency in AI infrastructure, and a track record of developer adoption and team building.

Leads the company’s growth organization across sales, marketing, partnerships, and customer success, owning go-to-market strategy, enterprise infrastructure deals, revenue operations, and team building. Requires 5+ years in growth or revenue leadership and experience selling technical infrastructure or developer tools.

Own customer onboarding, deployment, account health, and operational systems for AI infrastructure customers. The role requires 2–5 years in customer success, technical account management, operations, or a similar cross-functional function, with strong technical communication and process-building skills.

Own enterprise customer relationships for an AI infrastructure platform, combining technical partnership on training and inference workloads with renewals, expansion, capacity planning, and incident coordination. Requires 3–6 years in customer success, technical account management, solutions engineering, or an adjacent infrastructure role.

Owns global GPU sourcing, compute economics, contracting, and strategic capacity decisions for an open AI infrastructure platform. The role requires deep AI compute market knowledge, large-scale commercial negotiation experience, financial judgment, and technical fluency across research and engineering workloads.

Build the company’s compute intelligence platform, including warehouse infrastructure, production pipelines, data models, dashboards, and AI-accessible analytics. The role requires 3+ years of data-focused engineering experience, strong Python and SQL skills, and cross-functional business judgment.

Own the financial and strategic architecture for global compute supply, including pricing, provider diligence, capital allocation, and margin models. The role requires 4+ years of finance or strategy experience, exceptional modeling skills, commercial judgment, and curiosity about AI infrastructure.

Develops reinforcement learning, post-training, and agent systems that advance model reasoning and support real-world workflows. The role combines applied research with scalable training infrastructure, evaluations, and production deployment.

Build and deploy custom agent environments, evaluation systems, and post-training workflows for strategic customers using Prime Intellect’s Lab platform. The role combines applied research, technical customer engagement, and production delivery across agentic AI, reinforcement learning, and LLM evaluation.

Customer-facing applied research role focused on building AI agents, evaluation systems, and post-training workflows for frontier models. The role combines reinforcement learning, distributed infrastructure, applied data, and close collaboration with customers and research teams.

The foundational security hire will own security architecture, threat modeling, infrastructure and AI-specific defenses, incident response, and compliance for a frontier AI platform. The role requires 5+ years in security engineering plus expertise in cloud, Kubernetes, distributed systems, Python, and Rust or another systems language.

Own the intersection of customer discovery, AI product strategy, and revenue for a frontier post-training infrastructure platform. The role requires strong technical judgment, commercial execution, excellent communication, and comfort shaping a category before the product motion is fully defined.

Leads strategic customer deployments for frontier AI infrastructure, translating complex workflows into evaluations, environments, post-training initiatives, and production systems. The role combines technical customer ownership, applied AI strategy, cross-functional research partnership, and revenue responsibility.