Senior Machine Learning Engineer

Overview

Join a pioneering drug discovery company at the forefront of revolutionising healthcare through cutting-edge machine learning and AI technologies. As a Senior Machine Learning Engineer, you will have the opportunity to make a significant impact on the future of drug discovery by leveraging your expertise in machine learning algorithms and data analysis.

In this role, you will collaborate closely with cross-functional teams of biologists, chemists, and data scientists to develop innovative solutions to complex problems in drug discovery.

Responsibilities:
• Lead the design, development, and implementation of machine learning models and algorithms to analyse biological and chemical data for drug discovery projects to design better molecules.
• Utilise your expertise in deep learning, natural language processing, and other advanced machine learning techniques to extract insights from large-scale biological and chemical datasets.
• Work closely with interdisciplinary teams to identify… key challenges in drug discovery and develop novel machine learning approaches to address them.
• Implement scalable and efficient algorithms for processing and analysing high-dimensional biological and chemical data, including genomics, proteomics, metabolomics, and chemical compound libraries.
• Collaborate with software engineers to deploy machine learning models into production systems and integrate them into our drug discovery pipeline.
• Stay up to date with the latest advancements in machine learning, bioinformatics, and computational chemistry, and contribute to the company’s intellectual property through publications and patent applications.

Background:
• Master’s or Ph.D. degree in Computer Science, Bioinformatics, Computational Biology, or a related field.
• Strong background in machine learning, with 5+ years of hands-on experience in developing and deploying machine learning models for real-world applications.
• Proficiency in programming languages such as Python, R, or Julia, and experience with machine learning libraries such as TensorFlow, PyTorch, or scikit-learn.
• Experience in Deep Learning is required, particularly with intricate and expansive datasets such as biomedical imaging, graph-structured data, and physics simulations, ideally in a production setting.
• Proficiency in collaborative coding is essential, including familiarity with Git, bash, and either cluster computing or cloud providers.
• Excellent communication and teamwork skills, with the ability to collaborate effectively with cross-functional teams of scientists and engineers.
• Strong problem-solving skills and a passion for applying cutting-edge machine learning techniques to solve challenging problems in drug discovery.

Join this team and play a key role in shaping the future of drug discovery through the power of machine learning and AI. If you are passionate about leveraging machine learning to accelerate drug discovery, I’d love to hear from you!

Following your application Filipa Englefield, a specialist Biotech will discuss the opportunity with you in detail. She will be more than happy to answer any questions relating to the industry and the potential for your career growth. The conversation can also progress further to discussing other opportunities, which are also available right now or will be imminently becoming available. This position has been highly popular, and it is likely that it will close prematurely. We recommend applying as soon as possible to avoid disappointment.

Please click ‘apply’ or contact Filipa Englefield for any further information.

Filipa Englefield

Recruitment Consultant – EMEA

Email: fenglefield (@) barringtonjames.com

Company:

Barrington James

Qualifications:

Language requirements:

Specific requirements:

Educational level:

Level of experience (years):

Senior (5+ years of experience)

Tagged as: Clustering, Data Analysis, France, Industry, Natural Language Processing, NLP