Build simulation and real-world environments for training and evaluating embodied agents.
Train long-horizon robots with RL, imitation learning, and world models under hardware constraints.
Run post-training experiments to find what works and share reusable open-source systems.
Prime Intellect builds the open superintelligence stack, making frontier AI infrastructure available to ambitious AI teams. With $150M in funding from top investors, they are a well-funded startup focused on open-source AI and decentralized training.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Design, run, and analyse large-scale RL post-training experiments such as RLHF and RL from verifiable rewards.
Research and develop methods that improve out-of-distribution generalization, including reward design, task diversity, and regularization.
Build held-out evaluations to measure generalization and catch reward hacking, and turn successful research into production training recipes.
Cohere is a leading security-first enterprise AI company building cutting-edge foundation models and end-to-end products for businesses. We are a global team of researchers, engineers, and designers passionate about their craft, headquartered in Toronto with offices worldwide.
Build and ship AI methods for federal research data with LLMs, NLP, RAG, knowledge graphs.
Benchmark AI against baselines and human reviewers to prove gains in accuracy, reliability, efficiency, cost.
Set standards for trustworthy AI and mentor data scientists through code review and guidance.
ARI builds AI methods for federal research-funding and administrative data, with clients including the NIH. It is a small multidisciplinary team of scientists, analysts, economists, and data scientists experienced with NIH data.
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.
Build, train, and evaluate machine learning models end to end, from data and experiment design through training and reporting.
Design reinforcement learning environments, reward functions, and verifiers, and fine-tune language models using methods like PPO, DPO, and GRPO.
Collaborate with domain experts, analyze datasets, and present findings clearly to both technical and non-technical audiences.
EnableComp provides specialty revenue cycle management solutions for healthcare organizations using its unified E360 RCM platform. It is a multi-year Top Workplaces recipient and has been named to the Inc. 5000 list of fastest-growing private companies for eleven years.
Own the vision for applied AI solutions across Reddit's business and technical functions.
Build AI applications, agents, and automations that solve real business problems.
Mentor engineers and set technical direction for AI-native workflows.
Reddit is a community of communities, hosting open and authentic conversations on the internet. With 100,000+ active communities and approximately 130 million daily active unique visitors, it is one of the internet's largest sources of information.
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.
Lead and accelerate the Applied White-Box Methods team's research agenda on AI safety.
Develop and evaluate white-box methods on realistic large-scale agentic coding tasks.
Publish findings and engage with the AI alignment community and external partners.
FAR.AI is a non-profit AI research institute dedicated to ensuring advanced AI is safe and beneficial for everyone. Since its founding in July 2022, it has grown to 50+ staff, published 40+ academic papers, and convened leading AI safety events.
Build the component layer around our layout synthesis engine, including API contracts, services, and evaluation gates.
Turn model retraining into a one-command job with built-in benchmarks and readable results for the whole team.
Own latency and cost budgets for learned capabilities and partner with infrastructure engineers on MLOps and deployment.
Higharc is a VC-backed startup that is changing how new homes are designed and built using spatial AI and generative floor plan technology. The company is fully remote, has raised over $175M, and values flexibility, collaboration, and asynchronous deep work.
Build and ship LLM-powered applications and AI agent workflows.
Design systems for reasoning, planning, memory, tool use, and multi-step execution.
Optimize AI systems for quality, latency, and cost, and establish production practices for observability and evaluation.
Gina's Tech Jobs is a technology recruiting firm that connects companies with engineering and IT professionals. They focus on remote and onsite placements, offering personalized recruitment services and career support.