Role Overview
You’ll fine-tine, research, and train AI models specific to lifescience and diagnostics. You’ll work on R&D projects that will have meaningful impact on how our customers capture data from instruments. You’ll automate data pipelines for lab results using AI and orchestration. Ultimately, this will feed into a memory layer that suggests scientists what transformations to use based on their assay type and instruments.
The project will directly feed into a meaningful AI full stack app for all diagnostic instruments on this planet. It will help scientists to get to sample results 70% faster and reduce 50% error rate in the process.
Key Responsibilities
Develop machine-learning models for experiment data.
Build Python services and APIs.
Integrate AI tools with lab workflows.
Collaborate with scientists to refine solutions.
Write clean, tested code.
Must-Have Qualifications
Bachelor’s or Master’s in CS, Engineering, Data Science, or related field.
0–3 years of hands-on AI/ML experience.
Proficient in Python and popular ML libraries (e.g., PyTorch, scikit-learn).
Experience with API development (FastAPI, Flask, or similar).
Strong problem-solving skills and attention to detail.
Legal right to work in Canada (valid work permit or protected status).
Recent graduate or early-career candidate.
Nice-to-Have
Familiarity with cloud platforms (AWS EKS, S3).
Exposure to lab data (CSV, JSON, instrument files).
Experience with CI/CD and containerization (Docker, Kubernetes).
Knowledge of natural-language processing or computer vision.
What We Offer
Competitive salary
Flexible hours and hybrid work.
Mentorship from experienced AI and biotech experts.
Access to Communitech and Velocity programs.
Health benefits and generous stock options.
Budget for training
Your Two Year Roadmap
Month 1-6, you will:
Enhance Recommendation AI
Use prompt engineering and AI pipelines with LLMs for better suggestions.
Aim for performance and scalability.
Scale API and GLUE Layer
Build strong ETL support for enterprise loads.
Build SDK framework for Scispot APIs
Introduce NLP for Instrument Integration
Offer script templates so scientists can process data easily.
Suggest Telemetry Improvements
Improve monitoring for infrastructure health.
Graphical Chain of Custody
Let users query sample journeys with prompts using graph database
Month 7-12, you will:
EKS Migration
Grow & Maintain AWS EKS cluster
Automated Testing
Increase backend unit test coverage.
MCP Layer for Recommendation
Allow AI agents to take simple actions for scientists.
Upgrade Search
Improve OpenSearch and vector databases.
Memory Layer for Agents
Reduce reliance on retrieval-augmented generation by building memory layer for AI agents
Month 13-24, you will:
Lead Core Application Team
Oversee tech vision, architecture, and development.
App Store for Instrument Connectors
Expose our instrument integrations in a user-friendly marketplace.
Why You Might Love This Role
You want to shape the future of scientific research.
You enjoy solving complex AI challenges.
You like leading from the front, mentoring, and guiding teams.
A chance to build next-gen AI tools for lab workflows.
Leadership role with a high level of autonomy.
Why You Might Not
You dislike fast-paced startup environments.
You prefer strictly defined roles.