👤 Who we are

We are a dedicated team at the forefront of AI and chemistry, working to accelerate the energy transition. We focus on discovering new chemicals and materials that can lead to more sustainable practices in sectors where the need for change is most urgent. To do this, we develop a modern AI-driven discovery platform for new materials & catalysts that optimize chemical reactions, significantly reducing CO2 emissions. As an early-stage startup backed by substantial funding (>10M$), we base our approach on state-of-the-art academic research to drive practical business solutions.

🚀 Mission Highlights

As a ML/Data Scientist for Chemistry, your role will be to build & improve in-house ML models for materials discovery and translate them into actionable insights for strategic applications (e.g. electrochemistry, ammonia cracking, alloys, etc.), which you will develop with our industrial and academic partners. This includes predictive models for materials property, generative models for 3D structures, active learning pipelines, etc. You will collaborate closely with our research and engineering teams (~20 people) to enhance the performance, scalability and impact of our AI-driven solutions, while also engaging with clients to answer their needs and deliver superior materials.

✨ Role & responsibilities

This position directly supports the company’s mission of discovering materials to optimize carbon intensive industries. You will be responsible for some of the following:

• Algorithms: Contribute to the development of predictive and generative ML models in collaboration with dedicated teams (e.g. MLIPs, GFlowNets, diffusion, LLMs, etc.)
• Evaluation: Continuously evaluate and optimize the performance of our ML models by building adapted metrics for catalyst generation, building upon the insights from our industrial and academic partners.
• Active learning: Participate in the active learning strategy and implementation process to improve sample selection and future model performance.
• Clients: deliver client-facing projects, applying our discovery pipeline to various application domains.
• Support lab experiments: help build ML models that predict the Structure—Process—Property relationship of high-throughput experimental labs, for certain given applications.

🤓 Expertise & skills

• 4+ years of experience in AI4Science, with a MS/PhD in machine learning or chemistry. In particular, training ML models and understanding their implications for the targeted application, ideally catalysis, batteries or material science.
• Programming: great knowledge of Python / Pytorch, Git and cloud computing.
• Excellent communication skills in English.
• Proven ability to work with interdisciplinary teams.
• Strong analytical skills and problem solving ability.
• Thrives in a fast-paced, evolving startup environment.

📅 Recruitment Process

• Interview with the hiring manager
• Technical (research) interview about machine learning, material science & chemistry
• Coding interview
• Final interview with the CS(cience)O

📍 Reporting & Job Location

You will report to the Chief Science Officer (CSO) of Entalpic and will be located in our Paris offices, with up to 2 days of remote work per week.

🏆 Compensation & benefits

We are a no-nonsense startup, where we favor a sustainable culture promoting work-life balance and good compensation over football tables and free food. We offer:

• A competitive salary
• Equity (BSPCE), to reflect the value you bring to Entalpic and to foster a shared journey
• Comprehensive health insurance (Alan blue)
• French level paid leave and time-off work
• Dynamic work setting. Although our preference is for in-person collaboration, we will be flexible with occasional remote work arrangements.
• A relocation package and thorough visa support.
• and more to come as we grow

Entalpic is dedicated to equal opportunity employment and fosters an environment that is open and respectful of diversity. All applicants are encouraged to apply, even if you don’t meet all above requirements. If you have passion for our mission and believe you can contribute, we want to hear from you.

ℹ️ Information

• Start: From September 2025