Job Title

Scispot, a rapidly growing Canadian startup, is revolutionizing biotech data infrastructure worldwide. Known as the super app for lifescience labs, we merge technology with biotech and AI. Join us to shape the future of biotech labs with real impact. Role Overview Youll fine-tine, research, and train AI models specific to lifescience and diagnostics. Youll work on R&D projects that will have meaningful impact on how our customers capture data from instruments. Youll automate data pipelines for lab results using AIand 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 AIfull 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 Build Python services and APIs. Integrate AI tools with lab workflows. Collaborate with scientists to refine solutions. Must-Have Qualifications Bachelors or Masters in CS, Engineering, Data Science, or related field. 03 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 Flexible hours and hybrid work. Mentorship from experienced AI and biotech experts. Access to Communitech and Velocity programs. Health benefits and generous stock options. Your Two Year Roadmap Month 1-6, you will: Enhance Recommendation AI Use prompt engineering and AIpipelines 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 AWSEKScluster Automated Testing Increase backend unit test coverage. 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 AIagents 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. Kitchener | Seattle | London | San Francisco | Montreal #J-18808-Ljbffr