Design and execute experiments in reasoning model training, post-training alignment, test-time scaling, and systematic model evaluation for crypto-native applications.
Review and synthesize recent academic literature from NeurIPS, ICML, ICLR, and ACL to inform ongoing research directions in reasoning, alignment, and agentic AI.
Implement model variants and evaluation protocols using PyTorch and the Hugging Face ecosystem, tracking experiments with Weights & Biases.
Design and validate trading factors from multi-source market, fundamental, and on-chain data.
Develop and optimize prediction models using machine learning and deep learning to enhance signal accuracy and stability.
Lead end-to-end strategy design, backtesting, and live deployment, owning P&L and risk performance.
Binance is a leading global blockchain ecosystem and the world’s largest cryptocurrency exchange by trading volume, trusted by over 300 million users in 100+ countries. With a flat structure and world-class talent, the company fosters a fast-paced, results-driven culture focused on innovation and financial inclusion.
Build the RL post-training stack end-to-end: rollout ingestion, reward computation, policy updates, and returning updated weights to the network.
Invent algorithms for asynchronous, high-latency, partially trusted generation, including staleness tolerance and off-policy corrections.
Ship the first decentralized post-trained models, building evals and taking the release from run to public artifact.
Pluralis Research is developing Protocol Learning, a decentralized approach to training and serving large models on consumer devices. We are a small, deeply technical team backed by Union Square Ventures, with a remote-first culture and team members spread globally.
Design end-to-end LLM evaluation plans for business scenarios such as dialogue and financial trading.
Build evaluation metric systems and rubrics to quantify model performance and drive improvement.
Lead construction of evaluation datasets, define dimensions, and ensure high-quality annotation standards.
Binance is a leading global blockchain ecosystem behind the world's largest cryptocurrency exchange by trading volume and registered users. Trusted by 300+ million people in 100+ countries, we offer a diverse range of digital-asset products and services.
Conduct applied research in machine learning, focusing on time-series forecasting and generative AI for supply chain planning.
Design and run experiments using real-world and benchmark datasets, evaluating models against strong baselines.
Collaborate with researchers and engineers to build prototypes and assess product potential for real-world applications.
Kinaxis is a global leader in modern supply chain orchestration, powering complex global supply chains with an AI-infused platform. We are a global team of over 2,000 employees with a best-in-class HQ in Ottawa, Canada, and we take our culture seriously.
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.
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.
Analyze and model large volumes of business data to build algorithmic systems for compliance and regulatory requirements.
Lead a high-performing Data Analyst team, designing complex visualizations and analytical models.
Collaborate with compliance areas to deliver impactful analytical use cases and support business stakeholders.
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 100+ countries, the company offers a flat-structure, results-driven culture with a remote-first work environment.
Develop agentic research systems to automate mechanistic model development for biochemical and physiological processes.
Design and train machine learning models for in-context learning and few-shot adaptation on molecular and tabular data.
Collaborate with chemists and biologists to drive drug discovery decisions using AI models.
PostEra is building an AI-first biotech, using its Proton AI platform to accelerate the discovery of new medicines for patients. The company has a minimalist organizational structure, celebrating individual achievement through proportional compensation and collaboration toward delivering cures.
Distributed pretraining: Implement and optimize model-parallel training on heterogeneous GPUs under low-bandwidth, high-latency links.
Performance optimization: Apply techniques that reduce communication overhead while maintaining model convergence in challenging network environments.
Elasticity and fault tolerance: Build robust checkpointing and recovery so runs survive node churn as participants join and leave.
Pluralis Research is a decentralized AI research company developing Protocol Learning to train large models on consumer devices across the internet. The team is world-class and deeply technical, backed by tier-1 investors, with a remote-first culture.
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 end-to-end ML systems from data and training to evaluation, inference, and deployment.
Build and evolve training, fine-tuning, and inference infrastructure for large models.
Partner with research and application engineering to turn model capabilities into product improvements.
Next Step Systems is an IT recruiting and staffing agency that connects companies with machine learning and technology talent. They specialize in placing candidates in remote and on-site roles across the United States and emphasize a fast-paced, results-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.
Drive down proving cost for zero-knowledge proofs of AI inference.
Build production-quality proof systems for frontier-scale models.
Own the path from research prototype to deployable verification tools.
SASH's Verification team builds and tests tools to verify international agreements about AI, prototyping new verification mechanisms and working with policymakers. They are a small, globally distributed team combining technical expertise with international AI policy experience.
Lead exploration and application of Large Language Models and Generative AI into core product lines.
Translate the latest research into high-performing systems that enhance customer experiences.
Collaborate with cross-functional teams to set strategy and deploy ML solutions with real business impact.
Replicant is the industry leader in voice AI for customer service, providing automated phone bots for enterprises like AAA and Fanatics. Founded in 2017, the company is backed by top-tier Silicon Valley investors, has offices in the SF Bay Area, Toronto, and New York, and maintains a distributed team across the US and Canada.
Build and maintain core infrastructure for Quora's ML platform, ensuring high availability, scalability, and performance.
Build and improve distributed systems serving ML models in production, from Large Recommendation Models to Large Language Models.
Work on GPU model serving, optimizing latency, throughput, and cost to support larger and more capable models.
Quora's mission is to grow the world's collective intelligence through two platforms: Quora for global knowledge sharing and Poe for AI agent collaboration. We are a remote-first company with passionate, collaborative, and high-performing global teams, rooted in transparency and experimentation.
Train, evaluate, and iterate on ML models for customer feedback tasks with rigorous experimentation.
Build and maintain LLM-powered features including retrieval pipelines, reranking systems, and insight generation.
Contribute to evaluation frameworks, semantic search, and collaborate with engineering on model integration.
We help large brands like Uber, Amazon, and Wise put customers at the centre of everything they do using our AI-powered Customer Experience Intelligence platform. Our collaborative, growth-driven culture values trust, ownership, and humility as we build the next generation of customer feedback technology.
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.
Participate in end-to-end product development across frontend and backend under senior engineer guidance.
Integrate AI coding tools like Cursor, Copilot, and Claude Code into daily development workflows.
Translate product requirements into working implementations with minimal frontend-backend handoff friction.
Binance is a leading global blockchain ecosystem and cryptocurrency exchange, offering trading, finance, education, research, payments, and institutional services. The company is trusted by over 300 million users in 100+ countries and operates with a flat, user-centric, results-driven culture.
Conduct in-depth research and analysis of crypto projects across various sectors.
Produce comprehensive project reports and risk assessments that provide a holistic understanding of each project.
Analyze, evaluate, and synthesize trends from internal data and public blockchain information.
Binance is a leading global blockchain ecosystem behind the world's largest cryptocurrency exchange by trading volume and registered users, offering products from trading and finance to education, research, payments, and institutional services. Trusted by over 300 million people in 100+ countries, we are a user-centric global organization with a flat structure and a results-driven workplace.
Work across all aspects of data from engineering to building sophisticated visualizations, machine learning models, and experiments.
Analyze and interpret PB-scale transactional, operational, and customer data using proprietary and open source tools.
Translate complex findings into simple visualizations and recommendations for operational teams and executives.
Binance is a leading global blockchain ecosystem behind the world's largest cryptocurrency exchange by trading volume and registered users. With over 300 million users across 100+ countries, it offers a flat, results-driven culture and a fast-paced, innovative environment.