Source Job

US

  • Advance foundational AI research by developing unified models of housing markets, consumer demand, and economic conditions.
  • Design sophisticated machine learning systems, including latent state-space models and causal inference methods, for market simulations.
  • Collaborate with research, engineering, product, and data teams to translate findings into production-ready AI capabilities.

Python PyTorch TensorFlow Causal Inference Machine Learning

20 jobs similar to Applied Research Scientist, World Model

Jobs ranked by similarity.

Asia

  • 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.

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, the company has a flat, results-driven culture and focuses on increasing the freedom of money and financial access worldwide.

$150,000–$300,000/yr
Global

  • 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.

$130,000–$200,000/yr
US

  • 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.

$130,000–$200,000/yr
US

  • 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.

$130,000–$200,000/yr
US

  • 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.

US Unlimited PTO

  • 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.

Global

  • 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.

US

  • 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.

Global

  • 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.

$130,000–$200,000/yr
US

  • 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.

$150,000–$350,000/yr
Global

  • Build and extend pretraining code to scale experiments into full training runs.
  • Evaluate model architecture changes and optimize training throughput and resilience.
  • Run controlled ablations and collaborate with data and evaluation researchers.

Prime Intellect is building an open superintelligence stack, providing the infrastructure and platform for frontier AI training and deployment. The company has raised $150M from top investors and boasts a mission-driven team working to decentralize AI.

$160,000–$190,000/yr
US

  • 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.

Asia

  • Design and manage search recommendation services and models to empower content ecosystem development.
  • Utilize machine learning-based personalization methods to enhance content matching and distribution efficiency.
  • Collaborate with content, business, and product teams to identify needs and define success metrics.

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 fosters a user-centric, flat-structure culture with a focus on innovation and collaboration.

Global

  • 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.

US 4w PTO

  • 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.

$175,000–$218,000/yr
US

  • Lead hands-on data science to turn revenue opportunities into production ML systems.
  • Apply causal inference, experimentation, and advanced analytics to guide product decisions.
  • Mentor data scientists and set technical best practices in a collaborative, remote-first environment.

This company builds consumer technology products serving over 100 million monthly active users, focusing on revenue growth through personalization, experimentation, and subscriptions. It operates with a remote-first, AI-native culture that values direct communication, integrity, and high-impact execution.

North America

  • Conduct research on enterprise agentic AI, including agent memory, continuous learning, safety, and privacy.
  • Leverage unique access to real enterprise deployments to test hypotheses and advance the state of the art.
  • Publish at top-tier venues and collaborate with cross-disciplinary teams to influence product decisions.

ServiceNow is the AI control tower for business reinvention, bringing together AI, data, and workflows to help 85% of the Fortune 500 work smarter. The company is a global leader with over 8,100 customers, building an AI-native culture where technology and talent are unstoppable together.

US

  • Lead the end-to-end machine learning lifecycle, from data preparation and model training to evaluation, inference, and deployment.
  • Build and optimize scalable training, fine-tuning, and inference pipelines for large-scale models on GPU infrastructure.
  • Establish production best practices for model quality, reliability, safety, and measurable performance improvements.

This company builds production-grade machine learning systems and large-scale GPU-powered inference pipelines. It is a fully remote team that values technical rigor, collaboration, and hands-on engineering.

US

  • 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.

$150,000–$350,000/yr
Global

  • 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.