Applied Science
Mistral AI
Applied Science
Mistral AI
Open-weight LLMs and enterprise AI deployment
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.
Mistral AI is seeking Applied Scientists and Research Engineers focused on time series. You will design, train, and deploy state-of-the-art time-series foundation models, and apply them to the most demanding forecasting problems in industry, from power grids and plants to trading desks.
Timestral, our family of time-series foundation models, ranked first on amongst all benchmarks at release (tech report: https://arxiv.org/pdf/2610.37585v1 ). The role has two sides: building the next generations of Timestral with our Science team, and taking them into production with our industrial and financial clients, adapted to their data. Working cross-functionally with both external and internal science, engineering, and product teams you will deliver high-impact AI solutions. We are made of researchers, engineers, product builders, ex-founders who love tackling the most complex real world problems in the industry.
Run pre-training, post-training and deploy state of the art time-series foundation models on clusters with thousands of GPUs.
Generate and curate large-scale time-series datasets, real and synthetic, and build evaluators and benchmarks for forecasting and other time-series tasks.
Push the frontier of Timestral: architectures, training recipes, scaling, and new capabilities such as anomaly detection, classification and embeddings.
Fine-tune and adapt Timestral on client data, in the cloud or on-premise, and benchmark it against the client's existing models.
Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment.
Collaborate with cross-functional teams to tackle complex use cases, including agents that combine Timestral with Mistral LLMs.
Manage research projects and communications with client research teams.
Fluent in English with excellent communication skills, at ease explaining complex technical concepts to both technical and non-technical audiences.
Expert with PyTorch or JAX.
Solid knowledge of modern deep learning and large language models: architectures, pre-training, post-training and evaluation.
Experience pre-training or fine-tuning time-series foundation models or large transformer models at scale.
Strong background in time-series modelling: probabilistic forecasting, multivariate series and covariates, and classical baselines (statistical models, gradient boosting).
Not afraid of contributing to a big codebase; finds their way around independently with little guidance.
Writes clean, readable, high-performance, fault-tolerant Python code.
Doesn't need roadmaps: moves independently and is comfortable with uncertainty.
Low-ego, collaborative and eager to learn.
Track record of success through personal projects, professional projects or academia.
Ex-founder or builder
PhD / Master in a relevant field (Machine Learning, Statistics, Applied Mathematics, Physics). Exceptional candidates from other backgrounds welcome.
Research on time-series foundation models: pre-training, scaling, synthetic data or evaluation.
Hands-on experience training or fine-tuning LLMs, building agents and tool use, or models that combine text and time series.
Industry experience in energy, industrial operations, telecom or finance, or experience deploying models for industrial clients.
Experience working on large code bases or large machine learning models at scale.
Contributions to a large open-source or industry codebase.
Publications in top academic journals or conferences.
Enjoys improving existing code: typing, tests, CI pipelines.
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.
Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy.
Open-weight LLMs and enterprise AI deployment
Mistral AI builds open-weight large language models and the tools to run them, along with inference infrastructure and enterprise products that let organizations deploy AI with control over data residency, customization, and the underlying stack. Its platform provides open-model architectures and a deployment stack for inference, governance, and integration that can run on‑premises or in the cloud. This openness and modular stack differentiate it from single-vendor hyperscalers by prioritizing data locality and flexibility. The company aims to enable reliable, customizable AI deployment at scale for businesses and public-sector customers across many countries.
Explore more opportunities at Mistral AI