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Deep Genomics logoDeep Genomics

Senior Research Scientist, Machine Learning (BioFM)

Toronto, Ontario, Canada · Hybrid

$175k–$200k/yr

Senior$237M raised

About Us Deep Genomics is at the forefront of using artificial intelligence to transform drug discovery. Our proprietary AI platform decodes the complexity of RNA biology to identify novel drug targets, mechanisms, and t…

Skills: Machine Learning, Biological Foundation Models, Deep Learning, PyTorch, Computational Biology

Deep Genomics logoDeep Genomics

Senior Research Engineer, Machine Learning

Toronto, Ontario, Canada · Hybrid

$175k–$200k/yr

Senior$237M raised

About Us Deep Genomics is at the forefront of using artificial intelligence to transform drug discovery. Our proprietary AI platform decodes the complexity of RNA biology to identify novel drug targets, mechanisms, and t…

Skills: PyTorch, Machine Learning, Deep Learning, Linear Algebra, Calculus

Deep Genomics logo

Senior Research Scientist, Machine Learning (BioFM)

Deep Genomics

Toronto, Ontario, Canada • Hybrid

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  • $175k–$200k/yr
  • Full-time
  • postgraduate degree
  • Stock Ownership, Health Insurance, Vision Insurance, Dental Insurance, Employee and Family Assistance Program, Flexible Hours
  • Posted 21d ago
  • ~40 hrs/week

Responsibilities

Lead the research, design, and training of Biological Foundation Models using massive-scale genomic and transcriptomic datasets. Collaborate with biologists to integrate biological priors into model architectures and mentor junior scientists to maintain technical excellence.

Requirements

Requires a PhD in Computational Biology, Machine Learning, or a related field with a proven track record of scaling AI models for complex biological data. Proficiency in PyTorch and experience with large-scale deep learning architectures like Transformers are essential.

Full job description

About Us


Deep Genomics is at the forefront of using artificial intelligence to transform drug discovery. Our proprietary AI platform decodes the complexity of RNA biology to identify novel drug targets, mechanisms, and therapeutics inaccessible through traditional methods. With expertise spanning machine learning, bioinformatics, data science, engineering, and drug development, our multidisciplinary team in Toronto and Cambridge, MA is revolutionizing how new medicines are created.

Opportunity


We are seeking an exceptional and creative Senior/Staff Machine Learning Scientist to lead and innovate within our core AI research team, specifically focusing on the creative building of Biological Foundation Models (BioFMs). You will pioneer novel deep learning architectures and pre-training paradigms that learn the fundamental language of the genome and cellular biology. Rather than just applying out-of-the-box ML to biological datasets, you will design the next generation of BioFMs from tackling complex -omics data at scale. If you are a first-principles thinker excited to bridge advanced ML with genome biology to solve high-impact, frontier problems in human health and drug discovery, this is a unique opportunity.



\nKey Responsibilities
  • Lead the creative research, architecture design, and training of Biological Foundation Models (BioFMs), on massive-scale genomic, transcriptomic, and single-cell datasets.
  • Collaborate closely with computational biologists and drug developers to integrate deep biological priors directly into model architectures and training objectives, ensuring our BioFMs capture fundamental and scientifically meaningful representations.
  • Rigorously implement, train, debug, and evaluate large-scale models to demonstrate scientific validity and drive progress on frontier problems in human health and genetic medicines.
  • Stay current with advancements in machine learning and computational biology research, identifying cross-disciplinary applications to solve real-world challenges.
  • Mentor junior scientists and engineers, fostering a culture of technical excellence and scientific curiosity through leadership and high-quality code review.
  • Share research findings through internal presentations and contribute to the scientific community via publications in top-tier venues.
Basic Qualifications
  • PhD (or evidence of equivalent level of expertise) with a strongly distinguished research focus in Computational Biology, Machine Learning, Computer Science, or a related quantitative field.
  • Deep understanding of modern deep learning and the creative building of foundation models, including CNNs, Transformers, and related sequence models (e.g., state-space models) specifically tailored for biological or genomic sequence data.
  • A demonstrated track record of building and scaling AI models for complex biological datasets (e.g., single-cell genomics, DNA/RNA sequences) from initial conception to production.
  • Proven ability to implement, train, and debug highly-performant deep learning models using frameworks like PyTorch.
  • Experience working with massive datasets and a deep understanding of the engineering and algorithmic challenges associated with scale.
  • Excellent communication skills, capable of discussing complex ideas seamlessly with both ML engineers and biological domain experts.
Preferred Qualifications
  • A strong track record of impactful research demonstrated through first-author publications in high-impact scientific journals (e.g., Nature, Science, Cell) or top-tier ML/CompBio conferences (e.g., NeurIPS, ICML, ICLR, ISMB, RECOMB).
  • 2+ years of relevant post-graduate experience at a leading industrial R&D lab or in a highly competitive academic environment building genomics AI.
  • Experience technically leading projects or mentoring junior researchers/engineers.
  • Proficiency with cloud computing platforms (e.g., GCP) for large-scale model training and experimentation.
  • Contributions to open-source projects demonstrating the ability to solve complex research problems in ML or computational biology.
What We Offer
  • A collaborative and innovative environment at the frontier of computational biology, machine learning, and drug discovery. 
  • Highly competitive compensation, including meaningful stock ownership.
  • Comprehensive benefits - including health, vision, and dental coverage for employees and families, employee and family assistance program. 
  • Flexible work environment - including flexible hours, extended long weekends, holiday shutdown, unlimited personal days.
  • Maternity and parental leave top-up coverage, as well as new parent paid time off. 
  • Focus on learning and growth for all employees - learning and development budget & lunch and learns.
  • Facilities located in the heart of Toronto - the epicenter of machine learning and AI research and development, and in Kendall Square, Cambridge, Mass. - a global center of biotechnology and life sciences.
\n

Deep Genomics encourages applications from all backgrounds who seek the opportunity to build the world's leading AI-driven genetic medicine company. 

 

If you have a disability or special need, accommodation is available on request for candidates taking part in all aspects of the selection process.

 

 

*This posting reflects a current vacancy. 

 

We offer competitive compensation aligned with local market benchmarks. The salary range for this role is $175,000 - $200,000, and reflects Canada-based roles; compensation may differ for U.S.-based candidates.

Related keywords

BioFMDeep GenomicsRNA BiologyDrug DiscoveryGenome BiologyOmics DataPyTorchGCPNeurIPSICMLICLRISMBRECOMBNatureScienceCell

About Deep Genomics

LinkedInVisit site
Industry
Biotechnology Research
Company size
51-200 employees
Founded
2014
Headquarters
Toronto
LinkedIn followers
30,383
Total funding
$237M

Deep Genomics collaborates across disciplines to solve hard molecular design and target biology problems historically requiring slow, empirical iteration. We can do this because of our Biological Foundation (BioFM) Model Platform - a single engine with lab-in-the-loop workflows, AI model development and refinement, fit-for-purpose training datasets, AI output dataset assets, screening technologies, information systems, and software systems. On this common architecture, we build, run and improve the world’s best Biological Foundation Models in an effort to transform the field of drug discovery - finding molecules and targets others would miss, and accelerating their development into life changing medicines for patients.

Offices: MaRS Discovery District, Toronto, CA

Artificial IntelligenceBiotechnologyGeneticsArtificial Intelligence (AI)Therapeutics
View all jobs at Deep Genomics

About Deep Genomics

LinkedInVisit site
Industry
Biotechnology Research
Company size
51-200 employees
Founded
2014
Headquarters
Toronto
LinkedIn followers
30,383
Total funding
$237M

Deep Genomics collaborates across disciplines to solve hard molecular design and target biology problems historically requiring slow, empirical iteration. We can do this because of our Biological Foundation (BioFM) Model Platform - a single engine with lab-in-the-loop workflows, AI model development and refinement, fit-for-purpose training datasets, AI output dataset assets, screening technologies, information systems, and software systems. On this common architecture, we build, run and improve the world’s best Biological Foundation Models in an effort to transform the field of drug discovery - finding molecules and targets others would miss, and accelerating their development into life changing medicines for patients.

Offices: MaRS Discovery District, Toronto, CA

Artificial IntelligenceBiotechnologyGeneticsArtificial Intelligence (AI)Therapeutics
View all jobs at Deep Genomics

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