Senior Machine Learning Engineer - Graph ML

BenchSci
London
6 months ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Data Engineer

Senior Data Engineer (Python/PySpark & SQL)

Senior RF Data Scientist / Research Engineer

Join to apply for the Senior Machine Learning Engineer - Graph ML role at BenchSci

Join to apply for the Senior Machine Learning Engineer - Graph ML role at BenchSci

We are looking for a Senior Machine Learning Engineer to join our Knowledge Enrichment team at BenchSci.

You will help design and implement ML-based approaches to analyze, extract and generate knowledge from complex biomedical data such as experimental protocols and from results from several heterogeneous sources, including both publicly available data and proprietary internal data, represented in unstructured text and knowledge graphs. You will work alongside some of the brightest minds in tech, leveraging state of the art approaches to deliver on BenSci’s mission to expedite drug discovery. Knowledge Enrichment is at the core of this challenge as it ensures we can reason over and gain insights from an extensive, accurate, and high quality representation of biomedical data.

The data will be leveraged in order to enrich BenchSci’s knowledge graph through classification, discovery of high value implicit relationships, predicting novel insights/hypotheses, and other ML techniques. You will collaborate with your team members in applying state of the art ML and graph ML/data science algorithms to this data.

You are comfortable working in a team that pushes the boundaries of what is possible with cutting edge ML/AI, challenges the status quo, is laser focused on value delivery in a fail-fast environment.

You Will:


  • Analyze and manipulate a large, highly-connected biological knowledge graph constructed of data from multiple heterogeneous sources, in order to identify data enrichment opportunities and strategies
  • Work with data and knowledge engineering experts to design and develop knowledge enrichment approaches/strategies that can exploit data within our knowledge graph
  • Provide solutions related to classification, clustering, more-like-this-type querying, discovery of high value implicit relationships, and making inferences across the data that can reveal novel insights
  • Deliver robust, scalable and production-ready ML models, with a focus on optimising performance and efficiency
  • Architect and design ML solutions, from data collection and preparation, model selection, training, fine-tuning and evaluation, to deployment and monitoring
  • Collaborate with your teammates from other functions such as product management, project management and science, as well as other engineering disciplines
  • Sometimes provide technical leadership on Knowledge Enrichment projects that seek to use ML to enrich the data in BenchSci’s Knowledge Graph
  • Work closely with other ML engineers to ensure alignment on technical solutioning and approaches.
  • Liaise closely with stakeholders from other functions including product and science
  • Help ensure adoption of ML best practices and state of the art ML approaches within your team(s).Participate in various agile rituals and related practices


You Have:


  • Minimum 3, ideally 5+ years of experience working as an ML engineer
  • Some experience providing technical leadership on complex projects
  • Degree, preferably PhD, in Software Engineering, Computer Science, or a similar area
  • A proven track record of delivering complex ML projects working alongside high-performing ML, data, and software engineers using agile software development
  • Demonstrable ML proficiency with a deep understanding of how to utilize state-of-the-art NLP and ML techniques
  • Mastery of several ML frameworks and libraries, with the ability to architect complex ML systems from scratch
  • Extensive experience with Python and PyTorch
  • Track record of contributing to the successful delivery of robust, scalable and production-ready ML models, with a focus on optimising performance and efficiency
  • Experience with the full ML development lifecycle from architecture and technical design, through data collection and preparation, model selection, training, fine-tuning and evaluation, to deployment and maintenance
  • Familiarity with implementing solutions leveraging Large Language Models, as well as a deep understanding of how to implement solutions using Retrieval Augmented Generation (RAG) architecture
  • Experience with graph machine learning (i.e. graph neural networks, graph data science) and practical applications thereof
  • This is complimented by your experience working with Knowledge Graphs, ideally biological, and a familiarity with biological ontologies
  • Experience with complex problem solving and an eye for details such as scalability and performance of a potential solution
  • Comprehensive knowledge of software engineering, programming fundamentals and industry experience using Python
  • Experience with data manipulation and processing, such as SQL, Cypher or Pandas
  • A can-do proactive and assertive attitude - your manager believes in freedom and responsibility and helping you own what you do; you will excel best if this environment suits you
  • You have experience working in cross-functional teams with product managers, scientists, project managers, engineers from other disciplines (e.g. data engineering).Ideally you have worked in the scientific/biological domain with scientists on your team
  • Outstanding verbal and written communication skills. Can clearly explain complex technical concepts/systems to engineering peers and non-engineering stakeholders
  • A growth mindset continuously seeking to stay up-to-date with cutting-edge advances in ML/AI, complimented by actively engaging with the ML/AI community


About BenchSci:

BenchSci's mission is to exponentially increase the speed and quality of life-saving research and development. We empower scientists to run more successful experiments with the world's most advanced, biomedical artificial intelligence software platform.

Backed by Generation Investment Management, TCV, Inovia, F-Prime, Golden Ventures, and Google's AI fund, Gradient Ventures, we provide an indispensable tool for scientists that accelerates research at 16 top 20 pharmaceutical companies and over 4,300 leading academic centers. We're a certified Great Place to Work, and top-ranked company on Glassdoor.

Our Culture:

BenchSci relentlessly builds on its strong foundation of culture. We put team members first, knowing that they're the organization's beating heart. We invest as much in our people as our products. Our culture fosters transparency, collaboration, and continuous learning.

We value each other's differences and always look for opportunities to embed equity into the fabric of our work. We foster diversity, autonomy, and personal growth, and provide resources to support motivated self-leaders in continuous improvement.

You will work with high-impact, highly skilled, and intelligent experts motivated to drive impact and fulfill a meaningful mission. We empower you to unleash your full potential, do your best work, and thrive. Here you will be challenged to stretch yourself to achieve the seemingly impossible. Learn more about our culture .

Diversity, Equity and Inclusion: We're committed to creating an inclusive environment where people from all backgrounds can thrive. We believe that improving diversity, equity and inclusion is our collective responsibility, and this belief guides our DEI journey. Learn more about our DEI initiatives .

Accessibility Accommodations: Should you require any accommodation, we will work with you to meet your needs. Please reach out to .

Seniority level

  • Seniority levelMid-Senior level

Employment type

  • Employment typeFull-time

Job function

  • Job functionEngineering and Information Technology
  • IndustriesSoftware Development

Referrals increase your chances of interviewing at BenchSci by 2x

Get notified about new Machine Learning Engineer jobs in London, England, United Kingdom.

London, England, United Kingdom 2 weeks ago

London, England, United Kingdom 5 days ago

London, England, United Kingdom $35,000.00-$46,000.00 1 month ago

London, England, United Kingdom 2 weeks ago

London, England, United Kingdom 5 days ago

London, England, United Kingdom 3 months ago

London, England, United Kingdom 3 weeks ago

Hemel Hempstead, England, United Kingdom 1 week ago

London, England, United Kingdom 2 days ago

Junior Software Engineer (Integration Team)

London, England, United Kingdom 1 day ago

London, England, United Kingdom 1 week ago

AI Research Scientist (Sequential Decision Making)

London, England, United Kingdom 1 month ago

London, England, United Kingdom 4 days ago

London, England, United Kingdom 2 weeks ago

London, England, United Kingdom 2 weeks ago

London, England, United Kingdom 3 weeks ago

London, England, United Kingdom £90,000.00-£120,000.00 1 month ago

London, England, United Kingdom 2 months ago

London, England, United Kingdom 4 months ago

London, England, United Kingdom 1 week ago

London, England, United Kingdom 1 week ago

London, England, United Kingdom 4 months ago

London, England, United Kingdom 1 week ago

London, England, United Kingdom 2 months ago

London, England, United Kingdom 1 month ago

London, England, United Kingdom 1 day ago

London, England, United Kingdom 1 day ago

London, England, United Kingdom 33 minutes ago

London, England, United Kingdom 2 weeks ago

London, England, United Kingdom 1 month ago

Software Engineer - Go & Python, Ruby or C#

London, England, United Kingdom 3 weeks ago

Senior Machine Learning Engineer (must be UK based)

London, England, United Kingdom 1 week ago

London, England, United Kingdom 2 months ago

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Products

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Jobs

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.