Senior Machine Learning Scientist, Deep Genomics
AI Foundation Model Specialist
+ Meaningful stock ownership
AI powered RNA therapy discovery
Be an early applicant
AI powered RNA therapy discovery
101-200 employees
Be an early applicant
+ Meaningful stock ownership
101-200 employees
Company mission
To untangle the complexity in RNA biology, and evaluates thousands of possibilities to identify the best therapeutic candidates.
Role
Who you are
- PhD or MSc with a strong research focus in Machine Learning, Computer Science, Statistics, Physics, or a related quantitative field
- Deep understanding of the theoretical underpinnings and practical application of modern deep learning, including architectures like Transformers and related sequence models (e.g. state-space models)
- Proven ability to implement, train, and debug highly-performant deep learning models using frameworks like PyTorch or JAX
- Experience working with large datasets and understanding the challenges associated with scale (even if not directly managing infrastructure)
- Strong analytical and problem-solving skills, with the ability to translate ambiguous scientific problems into tractable ML formulations
- Excellent communication skills, capable of discussing complex ideas with both technical and scientific audiences
- 2+ years of relevant post-graduate experience in an industrial R&D or applied science setting, applying advanced ML to solve complex scientific or technical problems
- Experience technically leading projects or mentoring junior researchers/engineers
- Demonstrated potential through strong PhD/MSc research, impactful projects, relevant internships, or open-source contributions
- Track record of impactful research demonstrated through first or senior author publications in top-tier ML or relevant scientific journals/conferences(e.g., NeurIPS, ICML, ICLR)
- Proficiency with cloud computing platforms (e.g., AWS, GCP) for large-scale model training and experimentation
What the job involves
- We are seeking a passionate and highly skilled Machine Learning Scientist with expertise in Foundation Models to join our core AI research team, focusing on developing and scaling our next-generation foundation models for biology
- You will work with domain area experts to explore fundamental research questions at the intersection of deep learning and biology, and apply the latest in AI research to unique, large-scale biological datasets (many terabytes) to develop models that push the state-of-the-art
- If you are excited by using your strong ML knowledge to work with others and to solve frontier problems in drug discovery, this is a unique opportunity
- Collaborate closely with computational biologists to integrate domain knowledge, define scientifically meaningful tasks, and translate biological challenges into ML frameworks. You will work together to formulate key scientific questions in biology that can be addressed through innovative ML/AI approaches and design computational experiments to test hypotheses
- Contribute to, and potentially lead (depending on level) research into novel deep learning architectures, training paradigms (e.g., self-supervised, multi-modal), and algorithms tailored for large-scale biological sequence data and related modalities
- Rigorously implement, train, debug, and evaluate models to demonstrate scientific validity and potential for downstream application
- Stay current with advancements in both machine learning and computational biology literature, identifying cross-disciplinary opportunities to solve real-world challenges
- Contribute to team knowledge sharing and code quality through documentation and code reviews
- Share research findings through internal presentations, and potentially external publications or conference presentations
- Your ML models will directly and immediately impact the creation of new genetic medicines for patients with unmet needs
- This is not a disjoint R&D division - your models will be front-and-center in collaborations with drug developers and with our established pharmaceutical partners
- Discovery of truly causal relationships in complex biological systems
- These can even predict the impact of ultra-rare events (like genetic variants only ever seen in a single patient) that break typical correlative ML paradigms
- Immerse yourself in genomics and drug discovery through daily collaboration with world-class bioinformaticians and biologists, quickly gaining the domain knowledge to maximize your ML innovation and impact (no prior biology expertise required)
- An opportunity to publish and present work at the forefront of foundation models for genome biology, with applications in medicine and drug discovery
Our take
Deep Genomics uses AI to analyse genetic data with the aim of discovering and producing RNA-based genetic medicines. The company is currently running a series of programs with the aim of advancing to clinical trials in the near future.
RNA medical technology has been in development for over 40 years but never became mainstream, but the launch of BioNTech / Pfizer’s Covid-19 vaccine threw it into the public spotlight. This is set to accelerate the production of more and more RNA-based therapeutics, supplemented by AI which can quickly mine dense biological data to better evaluate potential candidates.
With its financial backing in the hundreds of millions, Deep Genomics now intends to radically boost its headcount and roll out more therapeutic discovery programs.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
-22% employee growth in 12 months
Company
Funding (last 2 of 4 rounds)
Jul 2021
$180m
SERIES C
Jan 2020
$40m
SERIES B
Total funding: $236.8m
Company benefits
- Highly competitive compensation, including meaningful stock ownership
- Health, vision and dental coverage for employees and families
- Flexible vacation time
- Facilities located in the heart of Toronto, next to the university and hospitals
- Direct access by subway, car and bicycle
- Hundreds of restaurants with foods from around the world
- Regular social events for team members and their families
Company HQ
Discovery District, Toronto, ON
Leadership
Brendan Frey, Ph.D.
(CEO)Professor of Engineering and Medicine at the University of Toronto. Co-founded the Vector Institute for Artificial Intelligence. They have carried out pioneering work in the fields of deep learning, genomic medicine, and information technology.
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