BenchSci

BenchSci offers ASCEND, a science-first Generative AI R&D platform designed to unravel disease biology and act as an AI Assistant/Co-pilot for preclinical scientists. It aims to elevate…

AI PlatformBiotechDisease BiologyDrug DiscoveryGenAILife SciencesPharmaPreclinical Researchbenchsci.com

BenchSci

BenchSci offers ASCEND, a science-first Generative AI R&D platform designed to unravel disease biology and act as an AI Assistant/Co-pilot for preclinical scientists. It aims to elevate…

AI PlatformBiotechDisease BiologyDrug DiscoveryGenAILife SciencesPharmaPreclinical Researchbenchsci.com

HQToronto, CA

Team Size278

Open Jobs3

Total Funding$164M

Latest Fundraise3 years ago

Join the Team

Senior Machine Learning Engineer - (Omics and Graph Intelligence)

On-SiteToronto, ON, CA

On-Site • Toronto, ON, CA

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Software Engineer

InternshipLondon, GB

Internship • London, GB

We are looking for a Senior Machine Learning Engineer to join our growing R&D team.

You’re the perfect fit for this role if you are passionate about solving problems in NLP, have a

great appreciation for science and want to transform how it is done. Reporting into the

Engineering Manager, R&D.

Pay range: $160,000 - $210,000 CAD

We know compensation is an important part of choosing your next role. The range shown reflects our target hiring range, informed by market data, internal equity, and the role’s current scope. Often the mid-range is where we tend to fall, but individual offers may vary based on experience, skills, and the role scope.

You Will:

You Have:

Nice to Have:

- Research publications in ML, AI or bioinformatics.
- Experience with multi-omics integration or cross-modal biological learning.
- Prior work on biomedical knowledge graphs, graph neural networks, or hybrid symbolic-neural systems.
- Experience deploying ML models into production systems used by scientists.
- Experience building AI-powered scientific assistants or chat-based analytical tools.

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

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.

Build and deploy machine learning models over omics data (e.g. genomics, transcriptomics, proteomics, epigenomics, and multi-omics), capturing biological structure, variability, and experimental context.
Work with major omics and biomedical databases (e.g. gene, protein, pathway, interaction, and expression resources) to integrate heterogeneous biological signals into unified learning pipelines.
Develop and apply foundation models for biological data, including sequence-based, expression-based, and multi-modal models, adapting them to downstream scientific and product use cases.
Design ML systems that populate, enrich, and reason over a biological knowledge graph, connecting entities such as genes, proteins, pathways, phenotypes, diseases, and experimental evidence.
Apply graph-based methods tailored to biology, including graph embeddings, message passing, and network-aware learning, to model molecular interactions and biological systems.
Collaborate with BenchSci’s Science team to ensure models reflect biological constraints, experimental design, and domain nuance, not just statistical patterns.
Power downstream experiences by surfacing insights through semantic search, recommendation, and conversational AI / chat-based scientific assistants.
Improve scalability, robustness, and interpretability of models operating on large, sparse, noisy, and biased omics datasets.
Lead technical decision-making within the ML team, mentor other engineers, and help define best practices for applied ML in biomedical settings.
Own projects end-to-end, from data exploration and model prototyping to production deployment and monitoring.
Continuously improve the performance and scalability of ML models that are at the core of BenchSci’s products
Regularly investigating what technologies will best enable BenchSci to effectively generate use cases
Advocate for code and process improvements across yourteam, and help to define best practices based on personal industry experience and research
Participate in sprint planning, estimation and reviews. Take ownership of deliverables, and work with teammates to ensure high-quality deliverables

Bachelor’s degree or higher in Computer Science, Mathematics, Machine Learning, Bioinformatics, or a related field.
Leadership: 2+ years of tech lead experience in a production ML environment.
Hands-on experience working with omics data and omics derived resources, such as genomic sequences, expression matrices, protein data, or biological networks.
Familiarity with omics and biomedical databases (e.g. gene/protein annotations, interaction networks, pathway databases, expression atlases).
Experience with or strong interest in biological foundation models, such as sequence models, embedding models, or multi-modal models applied to molecular or cellular data.
Solid understanding of graph methods in a biological context, including knowledge graphs, molecular interaction networks, or pathway-level representations.
Experience applying NLP or LLM-based techniques to scientific text or integrating text-based evidence with structured biological data.
Strong experience with TensorFlow, PyTorch, and Omics processing libraries.
Comfort working across disciplines, collaborating closely with scientists, engineers, and product teams.
A team player who strives to see teammates succeed together.
A growth mindset, strong ownership mentality, and desire to work on scientifically meaningful problems.
You have a constant desire to grow and develop.