Senior Machine Learning Engineer
Red Cell PartnersSalary not specified
- Full Time
- Senior (5 to 8 years)
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Pharmaceuticals, Biotechnology, Artificial Intelligence, BioinformaticsIndustries
Requirements
Candidates should have 5+ years of experience in Technical Project Management, including leading complex, multi-stakeholder projects from planning through execution. They should possess proven experience working with ML or Data Science teams and familiarity with the ML lifecycle, including model training, evaluation, and deployment. Strong organizational and communication skills are required, along with experience working in agile, cross-functional teams. Comfort operating in a fast-paced, research-driven environment is also necessary.
Responsibilities
As a Senior Technical Project Manager, you will lead the planning, execution, and delivery of machine learning projects across internal R&D and strategic partnerships. You will drive quarterly and yearly project planning, establish and maintain robust project management practices, track progress across multiple initiatives, facilitate collaboration across teams, and ensure clear communication of project status. Additionally, you will manage and facilitate strategic collaborations with external partners, ensuring alignment and execution on ML and data-driven initiatives.
Skills
Machine Learning
Bioinformatics
Data Science
Genomics
Project Management
Cross-functional Collaboration
Drug Discovery
Model Deployment
Stakeholder Coordination
Deep Genomics
AI-driven drug discovery and development
About Deep Genomics
Deep Genomics focuses on drug development in the biotechnology sector by utilizing artificial intelligence to explore RNA biology and discover potential therapies for genetic conditions. The company's main product, the AI Workbench, employs data-driven predictions to identify new drug targets. This tool has evolved over time, with the latest version, AI Workbench 3.0, set to enhance its capabilities in targeting complex genetic diseases. Deep Genomics serves a diverse clientele, including pharmaceutical companies and research institutions, and generates revenue through the development and licensing of its AI Workbench. The goal of Deep Genomics is to accelerate the drug discovery process and improve treatment options for patients suffering from genetic disorders.
Key Metrics
Toronto, CanadaHeadquarters
2014Year Founded
$230.3MTotal Funding
SERIES_CCompany Stage
AI & Machine Learning, BiotechnologyIndustries
51-200Employees