_{20th August, 2025}

ML Engineer
London - Hybrid

A well-funded VC backed start up is on a mission to transform drug design through cutting-edge AI, making the process faster, smarter, and more efficient. They are building an advanced AI platform to solve real-world challenges in drug discovery, partnering with industry leaders to bring impactful solutions to life.

Machine Learning Engineer – Drive AI Innovation in Drug Discovery
  
We are looking for a highly skilled and motivated Machine Learning Engineer to join this exciting start up and help translate cutting-edge AI research into real-world impact in drug discovery. If you are passionate about applying machine learning to solve complex scientific challenges, this is an exciting opportunity to make a meaningful contribution to the pharmaceutical and biotechnology industries.

What You Will Do

• Work closely with cross-functional teams to integrate machine learning models into impactful scientific applications.
• Analyse large-scale biological and chemical datasets to uncover patterns and generate actionable insights.
• Develop a highly scalable machine learning platform to support the integration of advanced AI models into the drug discovery process.
• Design, build, and maintain scalable ML infrastructure to handle high-throughput data processing efficiently.
• Continuously evaluate and refine model performance, ensuring accuracy, reliability, and real-world applicability.
• Stay at the forefront of AI advancements in drug discovery, bringing the latest innovations into your work.

  
Requirements

• A Master’s or Ph.D. in Computer Science, Bioinformatics, Computational Biology, Cheminformatics, or a related field.
• Proven experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn in industry.
• Industry experience in pharmaceuticals, biotechnology, or scientific discovery.
• Strong programming skills in Python for machine learning and data processing.
• Familiarity with big data technologies such as Spark, Kafka, and Iceberg.
• Knowledge of data modelling, database design, and data warehousing concepts.
• Experience with data visualisation tools like Superset, Grafana, or Metabase.
• Strong problem-solving skills with the ability to work independently and as part of a collaborative team.
• Excellent organisational and time-management skills.
• A deep passion for drug discovery and a drive to make a real impact in the field.

  
If you are excited by the opportunity to apply machine learning to accelerate breakthroughs in drug discovery, we would love to hear from you. Please send over your CV and, if suitable, the KEMIO team will be in contact to organise a conversation!










Keywords;
ML / Machine learning / AI / Engineer / Engineering computer science / computer scientist / python / drug discovery / Chemistry / cheminformatics /Bioinformatics  Data Science / quantum mechanics / engineer / engineering / biotech / biotechnology /pharma / pharmaceuticals / London

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