(Intern) ML Scientist for Chemisty - @Entalpic

Breega; Paris; Hybride; EUR 60 000 - 80 000; Plein temps

Résumé du poste

An innovative startup in AI and chemistry seeks an ML Scientist for Chemistry Intern to enhance ML models for materials discovery. This role involves collaborating with interdisciplinary teams to develop predictive models and support client projects. Ideal candidates are pursuing an MSc or PhD in AI4Science with strong machine learning experience, particularly in materials science. The position offers a dynamic work environment and competitive salary with flexible arrangements in Paris.

Prestations

Competitive salary

Flexible work environment

Paid day off per month

Professional development opportunities

Qualifications

• Strong experience in machine learning & materials science.
• Ability to bridge the knowledge gap between teams.
• Thrives in a fast-paced startup environment.

Responsabilités

• Contribute to the development of predictive and generative ML models.
• Continuously evaluate and optimize the performance of ML models.
• Participate in the active learning strategy.

Connaissances

Machine learning

Materials science

Python

Cloud computing

Communication in English

Analytical skills

Formation

Currently pursuing MSc or PhD in AI4Science

Outils

PyTorch

Git

Description du poste

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 an ML Scientist for Chemistry Intern, your role will be to 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 & characterization, generative models for 3D structures and synthesis recipes, active learning pipelines, etc. You will collaborate closely with our research and engineering teams (~15 people) to enhance the performance, scalability, and impact of our AI-driven solutions, while also engaging with clients to address 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 appropriate metrics for catalyst generation, leveraging 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.
• Support lab experiments: Help build ML models that predict the Structure—Process—Property relationships in high-throughput experimental labs for specific applications.

Expertise & skills

• Currently pursuing MSc or PhD in AI4Science.
• Strong experience in machine learning & materials science, particularly training ML models and understanding their implications for targeted applications, ideally thermocatalysis or electrocatalysis.
• Programming: Knowledge of Python / PyTorch, Git version control, and cloud computing.
• Appetite to bridge the knowledge gap between machine learning and materials science teams.
• 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 (Chief Science) Officer

Compensation & benefits

We are a no-nonsense startup, where we promote a sustainable culture emphasizing work-life balance and good compensation over perks like free food. We offer:

• Competitive salary + full reimbursement of your transport card
• A dynamic and flexible work environment: Remote-friendly with at least 3 days in Paris offices per week (Station F)
• 1 paid day off per month
• Professional development opportunities: access to conferences and internal learning sessions

Entalpic is dedicated to equal opportunity employment and fosters an environment that respects diversity. All applicants are encouraged to apply, even if they don’t meet all the above requirements. If you are passionate about our mission and believe you can contribute, we want to hear from you.

Information

• Duration: 4-6 months
• Start: From September 2025

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