Develop RL algorithms for reasoning, coding, and long-horizon tasks.
Design and run scaling experiments to improve training recipes across model sizes.
Extend RL training frameworks for asynchronous workflows and reliability.
Prime Intellect builds the open superintelligence stack, offering a platform that unifies compute, training, and deployment for frontier AI teams. With $150M in funding and a mission-driven culture, they focus on open-source AI research and real infrastructure.
Build and post-train agents for scientific research, including literature search, code execution, and domain tool use.
Develop RL and multi-agent methods for proposing, testing, and critiquing hypotheses, with strong baselines and evaluation.
Design verifiers, reward signals, and reproducible experimental loops for scientific workflows, ensuring evidence-based improvements.
Prime Intellect builds the open superintelligence stack, providing infrastructure for frontier AI labs to train, evaluate, and deploy models at scale. The company has raised $150M from top investors and operators, and is building a culture focused on frontier research, real infrastructure, and go-to-market for a new category.
Design, build, and maintain robotic platforms, including sensor integration, calibration, and actuator control.
Develop the robotics software stack for perception, state estimation, motion planning, and control, plus simulation environments.
Deploy and optimize learned models on hardware with attention to latency, safety, and reliability.
Metacognition builds intelligent systems capable of learning, remembering, and reasoning over time. It is an early-stage startup with a highly collaborative, fast-moving environment where employees have meaningful ownership.
Train models and evaluate AI systems to deliver world-class AI to the warfighter.
Run experiments in reinforcement learning, pretraining, multimodal training, and related areas.
Work as a self-starter in a fast-paced Series-A startup, interacting with customers and owning projects.
EdgeRunner AI builds secure, edge-deployed AI that helps American warfighters make faster decisions and interact with robotic platforms using natural language. It's a Series-A startup with a remote-first culture and a team of researchers and ML engineers.
Own applied RL programs from ambiguous customer problem to deployed improvement loop.
Understand workflows, build environments and evaluations, run post-training experiments, and deploy results.
Work directly with customer researchers, engineers, and leaders, accountable for research result and practical impact.
Prime Intellect builds the open superintelligence stack, providing a full-stack platform for frontier-scale post-training of AI models. The company has raised $150M from top investors and is seeking builders who want to work at the intersection of frontier research, real infrastructure, and go-to-market.
Own the path from emerging research artifact to excellent open-source and product experience.
Build core open-source systems and shape researcher-facing features in our training platform.
Work with external researchers and contributors to turn fast-moving abstractions into stable public interfaces.
Prime Intellect is building the open superintelligence stack, providing infrastructure and a full-stack platform for post-training frontier AI models. The company has raised $150M in funding from prominent investors and aims to make open-source AI research fully reproducible and accessible.
Define and lead the Physical AI research agenda spanning robotics, learning, data, evaluation, and automation.
Build and mentor a world-class research team while partnering with leading AI and robotics labs.
Advance general-purpose robot learning and scalable data systems, bridging simulation and reality.
A rapidly growing, venture-backed AI company building human intelligence infrastructure for the AI economy. Backed by $40M+ in funding, they connect global experts with high-impact AI projects through a proprietary talent-matching platform.
Build post-training and evaluation systems for multimodal agents operating browsers and desktops.
Turn real workflows into environments, rewards, and experiments that drive reliable agent improvement.
Work directly with customers and research partners while maintaining a substantive research agenda.
Prime Intellect is building the open superintelligence stack, providing infrastructure for post-training frontier AI models. The company has raised $150M in funding and fosters a culture of ownership and collaboration for ambitious AI teams.
Design and build challenging evaluations and executable environments for coding and long-horizon agents.
Develop scoring logic and verifiers to detect reward hacks and trace failures through model outputs and harness code.
Build and scale RL data pipelines for generating and curating challenging coding and agentic tasks.
Prime Intellect is building the open superintelligence stack, providing infrastructure for post-training frontier AI models and open-source models trained for long-horizon tasks. The company has raised $150M from top investors and is a mission-driven team passionate about accelerating science and AI.
Develop AI methods and algorithms for reliable agents.
Design simulations and evaluations for agent behavior.
Partner with product and engineering to ship research.
The company builds an AI agent platform focused on making agents reliable in production. It is a research-driven environment with a collaborative, startup-oriented culture.
Develop and improve AI methods, algorithms, and systems across the lifecycle of reliable AI agents.
Create new approaches for simulating, evaluating, and optimizing agent behavior in real-world settings.
Turn research ideas into working systems, prototypes, and production-facing capabilities.
The company builds infrastructure that helps enterprises make AI agents more reliable in production. It is a technical and research-focused team working on AI methods and practical systems.
Develop and improve AI methods, algorithms, and systems across the lifecycle of reliable agents.
Create new approaches for simulating, evaluating, and optimizing agent behavior in real-world settings.
Turn research ideas into working systems, prototypes, and production-facing capabilities.
The company is a research-focused team developing methods and systems to make AI agents more reliable in production. It operates as a small team with a culture of original research, experimentation, and close collaboration with product and engineering.
Build quantitative-research environments, agents, and post-training methods for systematic decision-making.
Turn workflows into tasks, run experiments against real baselines, and deploy what works.
Work directly with customers and quantitative funds while maintaining a substantive research agenda.
Prime Intellect builds the open superintelligence stack for post-training AI, unifying compute, environments, evaluations, and deployment. They have raised $150M from top investors and are building a culture of ambitious, externally-facing applied research.
Coordinate real-time robot software, motion planning systems, and machine learning pipelines across multiple platforms.
Build and maintain data-labeling tools, perception systems, and compilers for robotics applications.
Deploy software in customer facilities and improve performance based on real-world operation.
They build software for AI-driven robots in production environments. As a Series A company, they maintain an early-stage culture that values ownership and adaptability.
Build reinforcement learning and agent environments for real customer and Frontier lab use cases, including task specifications, scoring, and evaluation.
Develop benchmarks and evaluation harnesses to measure model and data quality across accuracy, robustness, safety, latency, and cost.
Run fine-tuning, adapter, and other model experiments to evaluate how data and methods influence model behavior, and deploy local or self-hosted models for evaluation and inference.
Appen has been a leader in AI training data for over 30 years, specializing in human-generated data to train, fine-tune, and evaluate models across generative AI, LLMs, computer vision, and speech recognition. They support model development through an AI-assisted data annotation platform and a global crowd of over 1 million contributors in more than 200 countries, fostering a culture of innovation, collaboration, and humility over ego.
Design and implement state-of-the-art ML models and training pipelines for robotics.
Develop efficient data/training strategies and evaluation frameworks for rapid experimentation.
Collaborate with engineering to optimize training infrastructure and deployment.
We're revolutionizing real-world automation by making robotic systems accessible to everyone. Our AI-powered platform brings software automation to physical spaces, and we're a small startup team working across the stack to solve customer problems.
Build the Learning Gym, a sandboxed environment for training and evaluating AI agents on real Niural workflows with ground-truth reward signals.
Engineer verifiers, run reinforcement learning loops, and establish honest baselines to prove agent improvements generalize.
Write first-author research papers and internal technical reports, and represent the work externally through preprints and talks.
Niural is a global payroll, Employer of Record (EOR), Agent of Record (AOR), and Contractor Management platform. It is a relentlessly ambitious team focused on building foundational internet infrastructure for the AI era.
Build inference systems powering RL research, scaling toward 1–3T parameter models on NVL72 clusters.
Optimize rollout throughput, multi-node MoE inference, and weight-update overhead for long-horizon agents.
Collaborate with model researchers on architecture choices balancing model quality and execution cost.
Prime Intellect is building the open superintelligence stack, unifying compute, environments, and deployment for frontier-scale AI post-training. Backed by $150M in funding, the team is mission-driven and hard-working, focused on accelerating open AI research.
Building agents, environments, and post-training systems for real semiconductor design and verification workflows.
Designing rewards and evaluations that combine functional correctness with tool efficiency, robustness, and performance/power/area constraints.
Owning interactive environments where agents use EDA tools to modify designs, debug failures, and plan multi-step work.
Prime Intellect builds the open superintelligence stack, unifying compute, environments, evaluations, and deployment for frontier-scale AI post-training. The company has raised $150M in funding from top investors like Founders Fund and NVIDIA, fostering a culture of building at the intersection of research, infrastructure, and go-to-market.
Build and optimize RL infrastructure for large-scale training.
Improve efficiency across compute, memory, networking, and scheduling.
Design low-level optimizations, from kernels to runtime.
Prime Intellect builds the open superintelligence stack, providing full-stack infrastructure for frontier-scale AI post-training and deployment. The company has raised $150M from top investors and is mission-driven, focused on open-source AI and accelerating science.