Senior Applied AI/ML Engineer
TetraScienceSalary not specified
- Full Time
- Senior (5 to 8 years)
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Pharmaceuticals, Biotechnology, HealthcareIndustries
Requirements
Candidates should have 3+ years of experience as an ML Engineer, Software Engineer, or similar technical role focused on ML systems, hands-on experience with ML frameworks such as PyTorch, TensorFlow, or JAX, proficiency in Python with a strong grasp of software architecture and engineering best practices, and experience with containerization and orchestration tools like Docker and Kubernetes. They should also be able to mentor and elevate other team members' skills.
Responsibilities
As a Senior ML Engineer, you will build and scale ML workflows by collaborating with ML scientists and data scientists, enable experiment tracking and reproducibility by integrating model development workflows with tools like Weights & Biases, engineer robust data pipelines for scalability and reliability, prototype and iterate quickly on solutions, and promote software engineering best practices through high-quality code and CI/CD. You will also contribute to the design, development, and maintenance of core components of the AI platform, pushing the boundaries of drug discovery through thoughtfully engineered systems.
Skills
Machine Learning
ML pipelines
Model training
Evaluation frameworks
Experiment tracking
Data pipelines
Python
PyTorch
TensorFlow
JAX
Software engineering best practices
CI/CD
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