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.
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.
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 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 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.
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 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 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.
Drive all aspects of chip design, including Functional Specification, Micro-architecture, RTL development, and Synthesis.
Work closely with PD, DV, and software teams to achieve PPA goals, functional coverage, and optimal performance.
Debug silicon-level functional, timing, and power issues during bring up.
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs, delivering industry-leading training and inference speeds. It works with leading model labs and global enterprises, with recent partnerships including OpenAI, and fosters a simple, non-corporate culture that values individual beliefs.
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.
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.
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.