Senior Machine Learning Engineer - Graph ML
Senior Machine Learning Engineer - Graph ML

Senior Machine Learning Engineer - Graph ML

London Full-Time 43200 - 72000 £ / year (est.) Home office possible
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At a Glance

  • Tasks: Join our team to design and implement cutting-edge ML solutions for biomedical data analysis.
  • Company: BenchSci accelerates drug discovery with advanced AI, supporting top pharmaceutical companies and academic centres.
  • Benefits: Enjoy a collaborative culture, remote work options, and opportunities for personal growth and development.
  • Why this job: Be part of a mission-driven team that values innovation, diversity, and continuous learning in a fast-paced environment.
  • Qualifications: 3-5 years of ML engineering experience, strong Python skills, and a degree in a relevant field required.
  • Other info: Work with leading experts and contribute to impactful projects in the scientific domain.

The predicted salary is between 43200 - 72000 £ per year.

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, and 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 complemented 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, complemented 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.

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.

Accessibility Accommodations:

Should you require any accommodation, we will work with you to meet your needs. Please reach out to talent@benchsci.com.

Senior Machine Learning Engineer - Graph ML employer: BenchSci Analytics Inc.

BenchSci is an exceptional employer that prioritises the growth and well-being of its team members, fostering a culture of collaboration, transparency, and continuous learning. As a Senior Machine Learning Engineer, you will work alongside some of the brightest minds in tech, contributing to meaningful projects that expedite drug discovery while enjoying a supportive environment that values diversity and personal development. With a commitment to innovation and a strong focus on employee empowerment, BenchSci offers a unique opportunity to thrive in a cutting-edge field within the vibrant city of Toronto.
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Contact Detail:

BenchSci Analytics Inc. Recruiting Team

talent@benchsci.com

StudySmarter Expert Advice 🤫

We think this is how you could land Senior Machine Learning Engineer - Graph ML

✨Tip Number 1

Familiarise yourself with the latest advancements in graph machine learning and NLP techniques. Being able to discuss recent developments or breakthroughs in these areas during your interview can demonstrate your passion and expertise.

✨Tip Number 2

Network with professionals in the biomedical AI space, especially those who have experience with knowledge graphs. Engaging in relevant online communities or attending industry conferences can help you make valuable connections that might lead to referrals.

✨Tip Number 3

Prepare to showcase your problem-solving skills by thinking of complex ML projects you've worked on. Be ready to discuss specific challenges you faced and how you overcame them, as this will highlight your technical leadership capabilities.

✨Tip Number 4

Research BenchSci's mission and values thoroughly. Understanding their focus on accelerating drug discovery and how your skills align with their goals will allow you to articulate why you're a great fit for their team.

We think you need these skills to ace Senior Machine Learning Engineer - Graph ML

Machine Learning Proficiency
Graph Machine Learning
Natural Language Processing (NLP)
Python Programming
PyTorch Framework
Knowledge Graphs
Data Manipulation and Processing
SQL and Cypher
Model Deployment and Maintenance
Technical Leadership
Agile Software Development
Problem-Solving Skills
Communication Skills
Collaboration in Cross-Functional Teams
Understanding of Biological Ontologies
Experience with Large Language Models
Retrieval Augmented Generation (RAG) Architecture
Performance Optimisation
Attention to Detail

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, particularly with graph ML and biomedical data. Use specific examples of projects you've worked on that align with the job description.

Craft a Compelling Cover Letter: In your cover letter, express your passion for the role and BenchSci's mission. Discuss how your background in ML and experience with knowledge graphs can contribute to their goals, and mention any leadership roles you've held.

Showcase Technical Skills: Clearly outline your proficiency in Python, PyTorch, and any other relevant ML frameworks. Provide examples of how you've applied these skills in past projects, especially in relation to the full ML development lifecycle.

Demonstrate Communication Skills: Since the role requires collaboration with cross-functional teams, highlight your ability to communicate complex technical concepts clearly. Include examples of how you've successfully worked with non-engineering stakeholders in previous roles.

How to prepare for a job interview at BenchSci Analytics Inc.

✨Showcase Your ML Expertise

Be prepared to discuss your experience with machine learning frameworks and libraries, especially Python and PyTorch. Highlight specific projects where you delivered robust, scalable ML models, focusing on performance optimisation.

✨Demonstrate Knowledge of Graph ML

Since the role involves working with graph machine learning, be ready to explain your understanding of graph neural networks and their applications. Share examples of how you've used knowledge graphs in previous projects.

✨Communicate Complex Concepts Clearly

Practice explaining complex technical concepts in simple terms. This is crucial as you'll need to communicate effectively with both engineering peers and non-technical stakeholders during your time at BenchSci.

✨Emphasise Collaboration Skills

Highlight your experience working in cross-functional teams. Discuss how you've collaborated with product managers, scientists, and other engineers to deliver successful projects, showcasing your ability to thrive in a team-oriented environment.

Senior Machine Learning Engineer - Graph ML
BenchSci Analytics Inc.
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  • Senior Machine Learning Engineer - Graph ML

    London
    Full-Time
    43200 - 72000 £ / year (est.)

    Application deadline: 2027-06-19

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    BenchSci Analytics Inc.

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