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BenchSci
BenchSci

Senior Machine learning Engineer (GraphRAG)

Location

Remote restrictions apply
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Salary Estimate

N/AIconOpenNewWindows

Seniority

Senior

Tech stacks

Data
Data Science
Machine learning
+23

Permanent role
16 days ago
Apply now

We are looking for a Senior Machine learning Engineer (GraphRAG & Retrieval Tools) to join our Knowledge Graph Retrieval team.

You will help design and build robust, reusable retrieval tools and services that empower consumer teams to leverage our large-scale Knowledge Graph. You will be building the core platform that powers sophisticated Graph-based Retrieval-Augmented Generation (GraphRAG) and automated querying applications. You will work alongside some of the brightest minds in tech, enabling state-of-the-art approaches to data retrieval and reasoning. Your work is at the core of this challenge, ensuring our internal teams can easily and effectively build applications on top of our graph data.

Your primary focus will be to build tools that abstract the complexity of graph traversal and retrieval. This includes developing sophisticated models for automated querying, creating high-performance retrieval services, and building developer-friendly APIs and libraries.

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:

  • Design, build, and maintain scalable retrieval tools and services (APIs, libraries) for internal consumer teams, focusing on our Knowledge Graph.
  • Develop and optimize automated querying systems, including Text-to-Query models (e.g., Text-to-Cypher), to translate natural language questions into efficient graph queries, developing Cypher templates and query stitching.
  • Partner with consumer teams to understand their needs, provide high-quality and well-documented tools, and drive the adoption of your retrieval platform.
  • Own the end-to-end lifecycle of the ML models that power these tools, from data preparation and training to deployment, monitoring, and iteration.
  • Collaborate cross-functionally with data engineers, ML engineers, and product managers to build a cohesive and powerful retrieval ecosystem.

You Have:

  • Minimum 3, ideally 5+ years of experience as an ML engineer or data scientist with a proven track record of delivering complex ML projects.
  • A strong platform-building mindset: Experience building and maintaining ML-powered tools, APIs, or platforms for other developers or internal teams.
  • Deep, hands-on experience with Graph Data Science (GNNs, link prediction) and Knowledge Graphs (e.g., Neo4j, Neptune) using query languages like Cypher.
  • Strong, demonstrable experience with LLMs and RAG pipelines, with a specific focus or passion for query generation and retrieval optimization.
  • Mastery of the Python data science and ML ecosystem (Pandas, PyTorch, scikit-learn) and experience with the full ML development lifecycle. Experience deploying services (e.g., FastAPI, Docker) is a plus.
  • Degree (preferably PhD or Masters) in Computer Science, Data Science, or a related field.
  • Excellent communication and collaboration skills, with a customer-centric mindset for understanding and supporting your internal "consumer teams".

Benefits and Perks:

  • 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 top pharmaceutical companies and leading academic centers.

Our Culture:

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. 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] .

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

About BenchSci

👥51-200
📍Toronto, Canada
🔗Website

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How does BenchSci work?

BenchSci empowers scientists with the world’s most advanced biomedical AI to advance assets with fewer, more successful experiments

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