BenchSciBE

Lead Machine Learning Engineer

We’re resolving the complexity of disease biology to help advance your science.

BenchSci

Employee count: 51-200

United Kingdom only
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We are looking for a Lead Machine Learning Engineer to join our new Knowledge Enrichment team at BenchSci.
You will help design and implement ML-based approaches to analyse complex biomedical data such as experimental protocols and results from several heterogeneous sources, including both publicly available data and proprietary internal data, represented in unstructured text and knowledge graphs.
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. 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:

  • Analyse 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 at BenchSci.
  • Participate in and sometimes lead various agile rituals and related practices.

You Have:

  • 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.
  • 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, 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.

Benefits and Perks:

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!

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 [email protected].

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About the job

Apply before

Jul 03, 2024

Posted on

May 04, 2024

Job type

Full Time

Experience level

Senior

Location requirements

Hiring timezones

United Kingdom +/- 0 hours

About BenchSci

Learn more about BenchSci and their company culture.

View company profile

We’re resolving the complexity of disease biology to help advance your science.

Using AI and proprietary visual machine learning, we’ve built the world’s first evidence-backed map of disease biology. Because we believe that when scientists understand what has already been done, they can understand the feasibility of what is yet to be discovered.

We taught a computer to read and understand experiments like a biologist

Our founders Tom Leung, David Q. Chen, Elvis Wianda, and Liran Belenzon met at the U of T Creative Destruction Lab in 2015. Together they built, tested, and validated an AI solution to the antibody reproducibility crisis. This captured the attention of Google’s AI fund Gradient Ventures, who led BenchSci’s A-round and raised $10M to develop the technology and the business.

Then built an enterprise AI solution to antibody selection

In 2017, BenchSci launched its first application, AI-Assisted Antibody Selection, to help scientists reduce experimental failure. The solution used both experiment-specific text ML and proprietary vision ML models that could understand the type of experiment being conducted. Next, our team then built relationships between those data points with proprietary bioinformatics ontologies. Best of all, we made these results searchable in an intuitive user interface.

Now we power research at the world’s biggest institutions

Within three years, more than 4,300 leading academic research institutions and 16 of the top 20 pharma companies were using our AI solutions. More than 50,000 scientists began relying on BenchSci to support their experiment decisions.

Project Butterfly—The world’s first evidence-backed map of disease biology

What scientists discovered was that BenchSci and our visual ML had built the first objective map of the underlying biology of disease. So, working in secret with top partners and global pharma R&D leaders, we launched Project Butterfly—an attempt to use this transformative technology to solve the biggest challenges in pre-clinical research. iNovia and TCV supported this initiative with a $50M Series C round.

Our next step: ASCEND

The portfolio success platform developed during Project Butterfly was given the name ASCEND, as it is designed to take the discovery and development of medicine to new heights. It augments scientists by giving them an unmatched understanding of disease biology in a platform that democratizes that understanding in all therapeutic areas. With ASCEND, our aim is to increase the speed and yield of the R&D portfolio by multiples, not percentages.

Series D Funding

BenchSci announces the completion of its Series D funding round led by Generation Investment Management. The significant investment enables BenchSci to further enhance the AI-powered platform ASCEND, expand offerings, and continue to empower scientists with the tools they need to accelerate drug discovery and improve patient outcomes.

Employee benefits

Learn about the employee benefits and perks provided at BenchSci.

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Home Office Budget

BenchSci supports remote work with a $1000 CAD budget for employees to set up their home office.

Learning & Development

BenchSci invests in its employees' growth with a $2000 CAD annual budget for learning and development.

Unlimited Flex Time

Employees at BenchSci enjoy unlimited flex time, sick days, personal days, and time off for religious holidays.

Parental Leave Top-Up

BenchSci offers generous parental leave benefits with a top-up plan and paid time options to support new parents.

View BenchSci's employee benefits
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