BenchSci is hiring a
Lead Machine Learning Engineer, Remote - United Kingdom

Summary

BenchSci is seeking a Lead Machine Learning Engineer to join their Knowledge Enrichment team. The role involves designing and implementing ML-based approaches for analyzing complex biomedical data, collaborating with team members on applying state-of-the-art ML algorithms, and delivering robust, scalable, and production-ready ML models.

Requirements

• Minimum 5, ideally 8+ years of experience working as an ML engineer
• Minimum 1, ideally 3+ years technical leadership experience, including leading 5-10 ICs technically 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 engineers using agile software development
• Demonstrable ML proficiency with a deep understanding of how to utilise 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 successfully delivering 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
• Strong skills related to implementing solutions leveraging Large Language Models, as well as a deep understanding of how to implement solutions using Retrieval Augmented Generation (RAG) architecture
• Expertise in 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

Responsibilities

• Design and implement ML-based approaches to analyze complex biomedical data
• Collaborate with team members in applying state of the art ML and graph ML/data science algorithms to this data
• 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 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 at BenchSci
• Participate in and sometimes lead various agile rituals and related practices

Preferred Qualifications

• 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
• 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

Benefits

• An engaging remote-first culture
• A great compensation package that includes BenchSci equity options
• A robust vacation policy plus an additional vacation day every year
• Company closures for 14 more days throughout the year
• Flex time for sick days, personal days, and religious holidays
• Comprehensive health and dental benefits
• Annual learning & development budget
• A one-time home office set-up budget to use upon joining BenchSci
• An annual lifestyle spending account allowance
• Generous parental leave benefits with a top-up plan or paid time off options
• The ability to save for your retirement coupled with a company match!