BenchSci is hiring a
Senior Machine Learning Engineer
closedBenchSci
π΅ $120k-$180k
πRemote - United Kingdom
Summary
We are seeking a Senior Machine Learning Engineer to join our Knowledge Enrichment team at BenchSci. The role involves analyzing, designing, and implementing ML-based approaches for enriching the company's knowledge graph with a focus on delivering value in a fail-fast environment.
Requirements
- Minimum 3, ideally 5+ years of experience working as an ML engineer
- Degree, preferably PhD, in Software Engineering, Computer Science, or a similar area
- 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 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 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
Responsibilities
- Analyze and manipulate a large, highly-connected biological knowledge graph constructed of data from multiple heterogeneous sources
- Work with data and knowledge engineering experts to design and develop knowledge enrichment approaches/strategies
- 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 BenchSciβs 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
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
This job is filled or no longer available
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