LLM Research Engineer for Chemistry

Our company: Entalpic

We are a dedicated team at the forefront of AI and chemistry, working to accelerate the energy transition. Our focus is on discovering new chemicals and materials that can lead to more sustainable practices in sectors where the need for change is most urgent. Specifically, we develop a modern generative AI platform to discover new catalysts that optimize chemical reactions, significantly reducing CO2 emissions and thus making a substantial impact on the environment.

As an early-stage AI-driven startup backed by significant funding (>5m), we base our approach on state-of-the-art academic research to drive practical business solutions. We value clear communication and simplicity in our approaches, promoting a constant optimization mindset.

Join Entalpic to be part of a growing team, eager to learn and adapt, united by the belief that our technology can make a significant positive impact and contribute to transforming carbon-intensive industries for a sustainable future.

Co-founders: Mathieu Galtier, Victor Schmidt, Alexandre Duval

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.

Reporting & Job Location

You will report to the CTO of Entalpic and will be located in our Paris offices.

Mission Highlights

As a LLM Researcher for Chemistry, your role will be to develop new (Large) Language Models for targeted use-cases of interest related to materials science & discovery. You will be involved in both internal projects and open-source collaborations. You will collaborate closely with our research and engineering teams (~10 people) to enhance the performance, scalability and impact of this AI solution, 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:

ML algorithms: lead the internal fine-tuning of LLMs for materials science. Collaborate with other ML Engineers to develop custom multi-modal architectures (e.g. text+graphs, text+images etc.). Continuously evaluate and optimize the performance of these models by building adapted metrics.

Research: Stay current with the latest advancements in the field and contribute to a large open-source collaboration with key actors of the field.

Data pipeline: gather and construct adapted databases to fine-tune our LLM, including the efficient scrapping of (multimodal) data sources and extraction of structured data. 

Model Lifecycle Management: Oversee the full lifecycle of ML models within our platform infrastructure —including data collection, integration, versioning, maintenance, performance monitoring, debugging, reproducibility, and traceability.

Collaboration: Work closely with software developers, ML engineers & material scientists to learn and share knowledge.

Profile

M.S or PhD in Machine Learning or Computer Science, ideally with some background in materials science and associated datasets. 

Solid experience with NLP and LLMs, in particular with running large-scale fine-tuning of LLMs for specific tasks, with good software development skills.

Appetite to explore the material science domain and to accelerate discovery in this field. 

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.

Expertise

Data scraping & management: ability with scrapping multi-modal data from the literature to create meaningful databases from LLM fine-tuning. Familiarity with data structures and database systems to manage and process large datasets efficiently.

Machine Learning: understanding of ML theories and practices, especially related to LLMs pre-training and alignment. Experience with active learning, transfer learning, multi-modal architectures or reinforcement learning are considered pluses.

AI platforms: Experience with deploying and managing machine learning models, including familiarity with Pytorch and containerization technologies (e.g., Docker, Kubernetes). Experience with distributed training is considered a plus.

Programming: Excellent software engineering skills in Python, with experience in software development best practices and version control systems such as Git. Experience with other languages and softwares such as C++ / CUDA or parallel programming are considered pluses.

Material Science: be familiar with some concepts of physics and chemistry, to design several LLMs for different material science related use-cases. 

Compensation & benefits

We are a no-nonsense startup, where we favor a sustainable culture promoting work-life balance and good compensation over foosball 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.

and more to come as we grow!