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.
Fine-tune open-weight LLMs using SFT, LoRA/QLoRA, and post-training methods such as DPO and GRPO to shape model behavior for 50M+ users.
Diagnose model failures and turn them into experiments, building training data and evals that directly influence production models.
Ship to production, speed up the training loop, and collaborate with Product, Web, and DevOps teams.
EverAI is building the world's largest AI companionship platform, redefining relationships for millions. With ~100 people, it's a fully remote, hardworking team with an ownership-driven culture and a track record of scaling products from 0 to IPO.
Contribute to post-training and evaluation infrastructure for a novel multimodal AI system.
Fine-tune models using supervised and reinforcement learning approaches (e.g., SFT, RLAIF, RLVR).
Define custom metrics and develop tools to assess and mitigate AI-related risks in generative AI.
Sony AI is Sony's research organization using AI to unleash human creativity, working with gaming, entertainment, and music divisions. The Ethical Creative and Protective AI Lab operates as a globally distributed team across the U.S. and Canada, with some 900 million Sony devices in use worldwide.
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.
Conduct research on reinforcement learning algorithms for multimodal models, including diffusion-based approaches and unified frameworks.
Design and build scalable RL infrastructure and reward modeling to support distributed training and improve stability.
Develop benchmarking protocols, curate multimodal datasets, and advance next-generation RL paradigms for real-world applications.
Tether is a fintech company pioneering digital finance solutions, including the stablecoin USDT, and developing energy, data, and education products. The company is a fast, lean global team of top talent working remotely across the world, with a culture focused on innovation and transparency.
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 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.
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.
Develop, fine-tune, and optimize self-hosted large language models for personalized AI conversations.
Work across the full model development lifecycle, from dataset preparation to GPU-based experiments and production deployment.
Collaborate with cross-functional teams to enhance conversational quality, memory, and multilingual interactions.
This company builds innovative consumer-facing AI products powered by self-hosted large language models. They operate a remote-first culture across Europe, emphasizing collaboration, continuous learning, and technical excellence.
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.
Design, deploy, and optimize large-scale ML systems for retrieval, ranking, and LLM-powered features.
Lead ML projects from concept to production, improving answer relevance and user experience.
Collaborate with Product, Data Science, and Engineering teams to shape technical direction.
The hiring partner is a technology company focused on building advanced AI systems that help users discover relevant answers from large collections of online conversations. It values innovation, collaboration, and responsible AI development, offering a remote work environment within the United States.
Design multi-step LLM systems for reasoning, retrieval, planning, and tool use.
Own evaluation from offline benchmarks to online experiments and model-graded review.
Set quality, latency, and cost targets, and mentor senior engineers.
They build enterprise AI systems, specifically agent systems for large customers. As a late-stage, venture-backed company, they focus on shipping reliable AI to enterprise clients.
Own LLM and VLM support on Metis and Europa AIPUs, from studying new models to shipping them in the Voyager SDK.
Use AI coding agents daily to build, test, and verify your work, combining LLM/VLM knowledge with solid software engineering.
Productize results into supported Voyager SDK features with stable APIs, tests, documentation, and release gates.
Axelera AI is a deep-tech company creating the next-generation AI platform to advance humanity and improve the world. They have raised $450M, employ 250+ people (60+ PhDs) across 21 countries, and foster an open, innovative, and inclusive culture.
Develop and improve 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.
Partner with product and engineering teams to bring AI research into practical applications.
The company builds infrastructure for reliable AI agents in production, targeting enterprise workflows. It is a focused team of researchers and engineers working collaboratively on advancing agentic AI.
Design and build LLM-powered agents and workflows including orchestration, tool use, retrieval, structured extraction, and human-in-the-loop review.
Build evaluations with data labelers and subject matter experts, running them on every change to ensure reliability.
Make agents production-grade by implementing guardrails, observability, cost and latency optimization, and careful handling of sensitive health data.
CCC Intelligent Solutions Inc. is a leading cloud platform for the multi-trillion-dollar insurance economy, creating intelligent experiences for insurers, repairers, automakers, and more. With over 35,000 businesses using its technology, the company focuses on innovation and collaboration to keep lives moving forward.
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.
Design end-to-end LLM evaluation plans for business scenarios such as dialogue and financial trading.
Build evaluation metric systems, rubrics, and high-quality datasets with credible, reproducible conclusions.
Analyze model limitations, automate evaluation workflows, and collaborate to drive model improvement.
Binance is a leading global blockchain ecosystem behind the world's largest cryptocurrency exchange by trading volume and registered users. Trusted by over 300 million people in more than 100 countries, the company offers a fast-paced, results-driven culture with a flat structure and world-class talent.
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 and ship production AI features for the illumend platform, including document extraction, coverage validation, and AI assistants.
Design LLM pipelines across Python/FastAPI backends and React/TypeScript frontends.
Build evaluation sets and automated checks to improve model accuracy, quality, latency, and cost.
Left Field Labs is a creative technology agency that partners with ambitious brands to build digital and immersive experiences. Since 2008, it has worked with clients like Google, Amazon, and Meta in an equal-opportunity, collaborative culture.