Nacre Capital
AI

AI Engineer

Nacre Capital · En remoto, ES

Actively hiring Posted 29 days ago

Role overview

We were founded by Nacre Capital, a venture builder focused on AI within the life sciences. Nacre has an impressive track record in creating, building, and growing deep tech startups, including Face.com (acquired by Facebook), Fairtility, FDNA, and Seed-X.

What you'll work on

  • Design, adapt, and implement machine learning and classical algorithms from proof of concept (POC) to working prototypes.
  • Plan and conduct experiments to address critical business questions.
  • Develop and maintain model testing and statistical verification processes.
  • Implement data processing and training pipelines.
  • Extend existing machine learning and deep learning codebases and frameworks.
  • Thoroughly document POCs and experiments.
  • Plan and lead long-term research activities.
  • Assist in recruiting talent in the field.
  • Stay up-to-date with the latest developments in AI and machine learning.

What we're looking for

  • Proven track record in developing image/video processing and computer vision solutions.
  • 3+ years of experience as a machine learning engineer/researcher or in a similar role.
  • Proficiency with common Python machine learning frameworks (scikit-learn, SciPy, Matplotlib, PyTorch, etc.).
  • Strong understanding of data structures, data modeling, and software architecture.
  • Ability to write clean, robust, and efficient code.
  • Excellent communication and presentation skills in English.
  • MSc or PhD in Computer Science, Engineering, Mathematics, or a related field. Candidates with a B.Sc. degree and equivalent industrial experience are also encouraged to apply.

*Benefits

  • A track record of publications in top-tier AI conferences or journals.
  • Experience deploying machine learning/AI systems in production environments.
  • Familiarity with containerization technologies (e.g., Docker).
  • Knowledge of databases (SQL, MongoDB) and basic networking or message-passing protocols.
  • Experience with cloud platforms (Google Cloud Platform, AWS, Azure).
  • Proficiency with MLOps frameworks (DVC, MLflow, Metaflow, Databricks).
  • Familiarity with CI/CD tools (Jenkins, GitLab CI/CD, Screwdriver, Spinnaker, or similar).

Tags & focus areas

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Fulltime Remote Ai Ai Engineer Machine Learning Computer Vision