AI/ML Engineer

Job summary

Design, evaluate, and operationalize personalized health models using wearable, CGM, EHR, laboratory, and behavioral data, including defining data pipelines, training strategies, and structured outputs. Build evaluation frameworks and collaborate with product and engineering teams to deploy safe, useful models in mobile and privacy-preserving workflows.

Job details

Applied AI/ML Scientist - Interviews are onsite in Vancouver Location: Onsite Salary: $110K – $120K Location: This is onsite 5 days a week in downtown Vancouver. Note: Candidates need experience in the biomedical domain, and at least 6 years of work experience About the Role We’re looking for an Applied AI/ML Scientist to help design, validate, and operationalize Mimik’s health agents. This role sits at the intersection of research and product engineering, with a strong focus on experimentation, multimodal modeling, personalization, evaluation, and real-world deployment. You will work on models that turn physiological and behavioral data into safe, structured outputs that power Mimik’s member experience. Key Responsibilities Model Design: Design and evaluate models for Mimik’s on-device health agents across wearable, CGM, EHR, lab, and behavioral data. Translation: Translate emerging research into practical implementations for personalized health inference under mobile and edge constraints. Architecture: Define feature pipelines, training data strategy, personalization logic, and structured output schemas for agent outputs. Evaluation: Build experiments and evaluation frameworks for accuracy, safety, calibration, and member-level usefulness. Engineering Collaboration: Work closely with product and engineering to move promising models into production mobile workflows, including on-device inference and privacy-preserving deployment. Domain Focus: Contribute to model and dataset selection for key domains such as sleep, stress, and metabolic health. Requirements Experience: Strong applied ML / data science experience in time-series, multimodal, or physiological data. Frameworks: Experience designing experiments, evaluation frameworks, and model quality metrics. Technology: Experience with agentic LLM systems. Mindset: Ability to work across research and engineering, not just modeling in isolation. Nice to Have Experience with on-device / edge ML, quantization, or mobile deployment. Familiarity with wearable, CGM, EHR, or lab data. Experience integrating model outputs into product systems built on JavaScript / TypeScript platforms.

What you’ll do

Design, evaluate, and operationalize personalized health models using wearable, CGM, EHR, laboratory, and behavioral data, including defining data pipelines, training strategies, and structured outputs. Build evaluation frameworks and collaborate with product and engineering teams to deploy safe, useful models in mobile and privacy-preserving workflows.

Requirements

Candidates need at least six years of work experience, biomedical-domain experience, and strong applied machine learning or data science experience with time-series, multimodal, or physiological data. They should have experience designing experiments and evaluation frameworks, working with agentic LLM systems, and collaborating across research and engineering.

Listed skills

• Évaluation · Preferred
• Health · Preferred
• Training · Preferred
• Teams · Preferred
• Time · Preferred
• Accuracy · Preferred
• Collaboration · Preferred
• JavaScript · Preferred
• Machine learning · Preferred
• Production · Preferred
• safety · Preferred
• TypeScript · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Applied Machine Learning
• Data Science
• Time-Series Modeling
• Multimodal Modeling
• Physiological Data Analysis
• Experiment Design
• Model Evaluation
• Model Quality Metrics
• Agentic LLM Systems
• Personalization
• On-Device Inference
• Edge Machine Learning
• Quantization
• Mobile Deployment
• Wearable Data
• JavaScript/TypeScript Integration

Job areas

• Technology
• Healthcare
• Data & Analytics
• Science & Research
• Software

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