Role overview

Machine Learning Engineer II

Requirements and responsibilities

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Here's what you'll do:

  • Represent Informatics as the subject matter expert in cross-functional initiatives, collaborating closely with scientists, data teams and technical stakeholders.
  • Identify and deliver solutions where computational and AI-driven approaches can improve efficiency, decision making, and knowledge utilization across complex workflows.
  • Design, develop and deploy production-ready AI-enabled applications that integrate structured and unstructured data for scalable use.
  • Build and implement retrieval-augmented systems (RAG), semantic search frameworks, and embedding-based data workflows to enable intelligent information retrieval.
  • Develop conversational AI interfaces and agentic architectures that automate knowledge-intensive tasks and support user interaction with complex datasets.
  • Research, design and develop machine learning algorithms, tools and systems;
  • Write structured, tested, readable and maintainable code, as well as participate in code reviews to ensure code quality and distribute knowledge for existing and new tools that allow us to extract, analyze, visualize and produce valued added insights of data for our customers;
  • Independently pursue research projects, implement novel computational workflows and support a dynamic multi-disciplinary team focused on moving projects from the hit identification stage to the discovery of candidates;
  • Perform statistical analysis and fin-tuning using test results;
  • Be actively involved in digital transformation projects and data governance objectives working closely with IT and scientific teams;
  • Ensure proper documentation of workflows, reports, tools, and analyses of the Research Informaticsโ€™ team;
  • Provide transparency and regular communication on project status, potential roadblocks for execution, and new strategies with Technology Sciences leadership;
  • Ensure project activities align with Eurofins policies, procedures and methodologies

The ideal candidate:

  • Degree in computer science, data science, computational chemistry, bioinformatics or related field.
  • At least 2 years of experience in building and deploying production ready AI-enabled research applications and workflows.
  • At least 2 years programing experience in Python, TypeScript, and full stack application development (Python, FastAPI, React, Streamlit).
  • Consolidated knowledge on prompt engineering, context engineering LLM frameworks, agentic frameworks, APIs and libraries.
  • Extensive knowledge and experience using chemical and bioinformatics libraries preferably in a drug discovery environment.
  • In depth knowledge of relevant public and proprietary databases, methods and tools.
  • Skilled with relational, non-relational, big data and big data analytics databases.
  • Deep knowledge of math, probability, statistics and algorithms.

The ideal candidate:

  • Ph.D. in Cheminformatics, Bioinformatics or related discipline;
  • Experience with Azure, AWS cloud infrastructure and services.
  • Experience in containerization, orchestration and workflow automation tools such as Docker, Kubernetes and Nextflow.
  • Experience in finetuning and training LLM models.
  • Experience in developing computer vision models using PyTorch.
  • Ability to work in the U.S. indefinitely without sponsorship

The ideal candidate:

  • Excellent full time benefits including comprehensive medical coverage, dental, and vision options
  • Life and disability insurance
  • 401(k) with company match
  • Paid vacation and holidays
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Browse stack
FocusMachine Learning EngineeringRole area
Seniority signalMiddleCandidate level
StackAWS, Azure, DockerPrimary skills
Location41 accepted countriesEligibility

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