Senior Machine Learning Engineer, Deep Genomics
Offers stock ownership
AI powered RNA therapy discovery
Be an early applicant
AI powered RNA therapy discovery
101-200 employees
Be an early applicant
Offers 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
- 3+ years of experience working as an ML Engineer, Software Engineer, or similar technical role focused on ML systems
- Hands-on experience with modern ML frameworks, such as PyTorch or TensorFlow
- Proficient in Python, with a strong grasp of software architecture, design patterns, and a deep understanding of engineering best practices
- Experience with containerization and orchestration tools, such as Docker and Kubernetes
- Ability to mentor and elevate other team members' skills
Desirable
- Track record of shipping ML prototypes to production in fast-paced, iterative environments (e.g. startups or research-heavy teams)
- Familiarity with ML workflow orchestration and tracking tools, such as Weights & Biases, Metaflow, MLFlow, Kubeflow, Ray, or similar tools
- Proficiency with cloud providers (preferably GCP), including managing compute, storage, and infrastructure for ML workloads
- Experience working with biological or genomic data and applications
What the job involves
- As a Senior ML Engineer, you bring deep expertise in building robust production-grade machine learning systems and infrastructure
- You’ll lead the design, development and maintenance of core components of our AI platform – spanning training pipelines, scalable inference, evaluation frameworks, experiment tracking and reproducible tooling
- Collaborating closely with teams across engineering, machine learning, and biology, you’ll help push the boundaries of drug discovery through thoughtfully engineered systems
- Build and scale ML workflows: Collaborate closely with ML scientists and data scientists to design, implement and maintain reliable systems for model training, evaluation, and inference
- Enable experiment tracking and reproducibility: Integrate model development workflows with tools such as Weights & Biases
- Engineer robust data pipelines: Develop and maintain data ingestion and processing pipelines for scalability, reproducibility, reliability
- Prototype and iterate quickly: Partner with stakeholders to rapidly develop proof-of-concepts
- Promote software engineering best practices: Drive high standards in code quality, modular design, testing and CI/CD
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Insights
-22% employee growth in 12 months
Company
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
Funding (last 2 of 4 rounds)
Jul 2021
$180m
SERIES C
Jan 2020
$40m
SERIES B
Total funding: $236.8m
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