Remote Jobs RockRemote Jobs Rock

LLM Scientist, AI for Science

πŸ•’ 13 days ago
Large Language ModelsDeep LearningAgentic AIPytorch
Apply Now

πŸ“œ Description

  • Specialize in developing and optimizing large language models (LLMs) and agentic AI.
  • Participate in end-to-end training of LLM-based solutions focusing on scalability and scientific applicability.
  • Design workflows to accumulate high-quality scientific data at scale.
  • Collaborate with domain scientists to identify AI opportunities and refine models.
  • Contribute to infrastructure improvements for model training in scientific contexts.

πŸ› οΈ Requirements

  • Strong background in LLMs, deep learning, or agentic AI with real-world application experience.
  • Familiarity with the latest advancements in LLM architectures.
  • Hands-on experience with PyTorch, TensorFlow, or JAX.
  • Ability to understand at least one Natural Science domain at a high level.
  • Proficiency in scientific computing and software best practices.

✨ Benefits

  • Healthcare coverage
  • Parental leave
  • Retirement plans
  • Relocation support
  • Wellness programs
  • Meal and transportation allowances
  • Other location-specific perks
Full job description

About Mistral

Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms.

We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.

About the Role

We are hiring an LLM Scientist to push the boundaries of AI-driven scientific discovery. You will specialize in developing and optimizing large language models (LLMs), agentic AI, and deep learning frameworks to solve open problems in the natural sciences: Biology, Chemistry, Physics, and/or Materials Science. Your work will empower scientists with cutting-edge AI tools and accelerate research through:

  • Model-centric innovation: Improving LLMs’ capabilities to tackle complex scientific problems (e.g., literature synthesis, autonomous experimentation, rigorous derivations).

  • Cross-disciplinary collaboration: Partnering with Natural sciences domain experts to translate AI advancements into real-world scientific impact.

What you will do

  • AI/ML Research: Participate in end-to-end training of LLM-based solutions, with a focus on scalability, generalization, and scientific applicability.

  • Data creation: Design original workflows to accumulate high quality scientific data at scale, either through synthetic or crowd sourced pipelines.

  • Algorithm Design: Use and improve reinforcement learning, or agentic systems tailored to Natural sciences challenges (e.g., modeling resolution, material property prediction, advanced data analysis and coding).

  • Interdisciplinary Bridge: Work closely with domain scientists to identify AI opportunities and refine models based on feedback.

  • Tooling & Infrastructure: Contribute to company infrastructure to improve usability for model training in scientific contexts and open-source AI tools for science for non-AI experts.

  • Autonomous Innovation: Set a research agenda for AI in science, exploring high-risk/high-reward ideas.

Β 

What We're Are Looking For

  • AI/ML Expertise: Strong background in LLMs, deep learning, or agentic AI, with a track record of applying these to real-world problems (publications, open-source contributions, or deployed systems) – at the minimum extensive experience in computer science and ideally experience scaling synthetic data generation.

  • State-of-the-art Knowledge: Familiarity with the latest advancements in LLM architectures and post training.

  • Technical Depth: Hands-on experience with PyTorch/TensorFlow/JAX, model optimization, and scaling techniques (e.g., fine-tuning, RLHF).

  • Scientific Capability: Ability to understand 1 Natural Science domain at a high level (e.g., graduate level specialization + general undergrad knowledge) to design effective AI solutions.

  • Engineering Rigor: Proficiency in scientific computing (e.g., numerical methods, HPC) and software best practices.

  • Collaboration: Experience translating technical AI concepts for non-experts (e.g., scientists, engineers) and iterating based on user needs.

  • Mindset: Low ego, team player, and eager to tackle operational challenges (e.g., data pipelines, model deployment).

Motivational paragraph

When applying for the AI for Science team at Mistral, please describe in a short paragraph a potential project that you would like to contribute to the team, why it is challenging and interesting in general, and more specifically for Mistral. Please also highlight the specific skill set that you can bring to the team.

What We Offer

We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.

For the most up-to-date details on benefits available in your location, please refer to our Benefits page.

Privacy Policy

Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy.

Opera

AI Engineer

πŸ”₯ 20 hours ago
OperaπŸ‘₯ 1001 - 5000 employees🏒 Computer Software

Develop and extend an AI engine, create AI features, and research emerging technologies, applying Python, mathematics, and machine learning expertise to solve complex problems.

PythonArtificial IntelligenceLarge Language ModelsMachine Learning
Cogent Labs

AI Engineer

πŸ”₯ 23 hours ago
Cogent Labs🏒 Artificial Intelligence

Build and ship enterprise AI products by designing LLM coding-agent harnesses, evaluation benchmarks, and reliable production systems, while exploring model improvements and applied research.

LLM AgentsCoding AgentsAI EvaluationTypeScript
Wonderful

AI Enablement Engineer

πŸ•’ 3 days ago
WonderfulπŸ‘₯ 201 - 500 employees🏒 Internet

Combine hands-on AI engineering with technical teaching to onboard teams, lead customer and partner training, and help people build and deploy enterprise AI solutions independently.

πŸ“ πŸ‡©πŸ‡ͺ Germany - HybridπŸ’Ό Full-Time🎹 Mid-levelπŸ€– AI EngineerπŸ“’ πŸ‡©πŸ‡ͺ German RequiredπŸ“’ πŸ‡¬πŸ‡§ English Required
AI EngineeringSystem ArchitectureLLM IntegrationAI Agent Integration
Anthropic

Applied AI Engineer, Startups (Physical AI)

πŸ•’ 4 days ago
AnthropicπŸ‘₯ 10,000+ employees🏒 Research Services🀝 B2B

Advise physical-world startups on building products and engineering workflows with Claude, leading technical engagements, prototyping integrations, and developing evaluations and reusable solutions across hardware domains.

Applied AI EngineeringLLM-powered ApplicationsPromptingContext Engineering

Trusted by Remote Workers