Machine Learning Engineer for Materials Property Prediction

il y a 4 semaines

Paris, Île-de-France Breega Temps plein
About Entalpic

We are a pioneering team at the forefront of AI and chemistry, dedicated to accelerating 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 cutting-edge generative AI platform to discover new catalysts that optimize chemical reactions, significantly reducing CO2 emissions and making a substantial impact on the environment.

Role and Responsibilities

As a Machine Learning Engineer, you will be responsible for translating complex ML algorithms for materials property prediction from conceptual frameworks into robust, scalable models within our platform. You will collaborate closely with our research and engineering teams to enhance the performance, scalability, and impact of our AI-driven solutions.

  • Algorithm Development: Implement, evaluate, and optimize machine learning models for atomic graphs based on cutting-edge research and internal insights.
  • Model Integration and Management: Oversee the full lifecycle of machine learning models, including data collection, integration, versioning, and maintenance within our platform infrastructure.
  • Monitoring and Debugging: Efficiently track the performance of live models and develop debugging tools to swiftly resolve any issues.
  • Reproducibility and Traceability: Establish systems and practices ensuring that all experiments and models are reproducible and traceable.
  • Research: Stay current with the latest ML advancements in the field and suggest integrations that may improve the platform performance and capabilities.
  • Collaboration: Work closely with data scientists, chemists, and other engineers to understand requirements and deliver solutions that enhance our research capabilities.
Requirements
  • PhD or M.S: in Computer Science, Machine Learning, or a closely related field, with a focus on deep learning.
  • 3+ years of experience: in machine learning and software engineering-related positions which involved training DL algorithms (GNN, Transformers) in the cloud.
  • Excellent Communication Skills: in English.
  • Proven Ability: to work with interdisciplinary teams.
  • Thrives in a Fast-Paced Environment: in a fast-paced, evolving startup environment.
Expertise
  • Machine Learning: Deep understanding of ML theories and practices, especially related to reproducibility and scalability.
  • (Geometric) Graph Neural Networks: Experience in developing, training, and evaluating GNNs for 3D atomic systems (molecules, proteins, materials, etc.).
  • Programming: Proficient in Python, with experience in software development best practices and version control systems such as Git.
  • Data Management: Familiarity with data structures and database systems, both SQL and NoSQL, to manage and process large datasets efficiently.
  • AI Platforms: Experience with deploying and managing machine learning models, including familiarity with Pytorch and containerization technologies (e.g., Docker, Kubernetes).
Compensation and Benefits

We offer a competitive salary, equity (BSPCE), comprehensive health insurance (Alan blue), French level paid leave and time-off work, and a dynamic work setting. Although our preference is for in-person collaboration, we will be flexible with occasional remote work arrangements.

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