Genomics AI/ML Scientist — Predictive Healthcare

Socket.dev; Canada; Remote; CAD 134,000 - 170,000; Full time

Benefits offered by this job

Comprehensive Health Insurance

12 weeks Parental Leave

Well-Being Benefits

Flexible PTO

Remote options + home office stipend

Job summary

Helix is hiring an AI/ML Scientist to own pieces of modeling work on a clinical genomics dataset. You will train, evaluate, and report on models forecasting disease trajectories and extracting insights from clinical text.

Collaboration with bioinformatics, clinical, and engineering teams is key, with opportunities to present at conferences and contribute to scientific writeups. The role emphasizes writing readable experiment code, robust evaluation pipelines, and a strong foundation in

Qualifications

• MS or PhD in machine learning, computer science, statistics, computational biology, bioinformatics, or related field
• 2–5 years of applied ML experience beyond degree
• Solid Python skills and ability to write/troubleshoot training loops
• Experience with git, containers, cloud GPUs, and experiment tracking
• Familiarity with biology/clinical problem domain and curiosity to learn genomics

Responsibilities

• Own well-scoped pieces of a larger modeling effort: implement, train, evaluate, and report
• Write experiment code that can be read, rerun, and trusted
• Build and maintain evaluation pipelines and report results
• Investigate data quality issues in healthcare data
• Present results to team and leadership, and represent work externally
• Collaborate across bioinformatics, clinical, and engineering stakeholders
• Draft scientific writeups and carry results to papers or conferences

Skills

Python

Git

Containers

Cloud GPUs

Statistics

Biology interest

Communication

Learning from data

Education

MS or PhD in ML/CS/Biology/Quantitative field

Tools

PyTorch

Lightning

AWS SageMaker

Job description

Helix is hiring an AI/ML Scientist to own pieces of modeling work on a clinical genomics dataset. You will train, evaluate, and report on models forecasting disease trajectories and extracting insights from clinical text.

Collaboration with bioinformatics, clinical, and engineering teams is key, with opportunities to present at conferences and contribute to scientific writeups. The role emphasizes writing readable experiment code, robust evaluation pipelines, and a strong foundation in