Machine Learning Engineer, GenAI
Role summary
Altea Healthcare is seeking a Machine Learning Engineer specializing in GenAI to join their team in Burnaby, BC. This role focuses on developing, deploying, and scaling GenAI applications, emphasizing MLOps and software engineering best practices within the healthcare industry. The engineer will collaborate with cross-functional teams to drive products from conception to production, ensuring quality and scalability. Key responsibilities include writing production-ready code, testing, troubleshooting, and optimizing system architecture. The ideal candidate will have at least 2 years of post-education experience in ML or Software Engineering, with proven experience in deploying GenAI solutions on Azure and familiarity with frameworks like LangGraph and Langchain.
Job Title:
Machine Learning Engineer, GenAI
Company:
Altea Healthcare/Aarista Technologies
Location:
This role requires working onsite at our Burnaby, BC office
four days per week
, with one day per week working from home. (Hybrid)
We also consider exceptional candidates for remote work flexibility in Canada.
Compensation:
$145-170k CAD
ALTEA Healthcare is a leading healthcare organization committed to revolutionizing the delivery of outpatient and post‑acute care. We are seeking a Machine Learning Engineer to join our team. The ideal candidate will have a strong background in developing and shipping scalable GenAI solutions. We have shipped a suite of rich GenAI products, with many more exciting products on the way. As an important member of the AI team, this person will contribute significantly to designing, implementing, deploying, and iterating on AI/ML products that help care providers improve care delivery and quality for post‑acute patients.
Responsibilities:
- Develop and ship AI products, with a focus on scalability and monitoring.
- Collaborate with MLEs, front-end, and back-end engineers to deliver high-quality products/apps.
- Drive products from 0 to 1 (from business requirements to production deployment).
- Incorporate feedback from cross-functional teams and refine ML-driven applications through quick iteration cycles.
- Maintain best software engineering and MLOps practices within the healthcare industry.
- Document and optimize system architecture, design decisions, and codebase to facilitate future maintenance and enhancements.
Sample day-to-day work:
Including, but not limited to:
- Write, test, and debug production-ready code
- Review and approve PRs
- Troubleshoot and resolve production issues and user feedback
- Work with external teams (frontend, backend, product) to design/optimize AI products
- Scale products to more regions and end-users
- Update documentation and track progress on tickets
- Assist with ad-hoc scripts when needed
Core qualities that will thrive here:
- Ownership: Own project end-to-end, ensuring accuracy, timeliness, and alignment with business goals; drives clarity, follows through on commitments, manage dependencies from other teams, and be accountable for outcomes and quality.
- Problem solving: Enjoy identifying root causes, solving complex technical problems, and proactively proposing scalable improvements.
- Contribution to team: Actively supports teammates through PR reviews, collaboration, knowledge sharing, and constructive feedback.
- Product-driven mindset: Enjoy creating impactful products from 0 to 1 in a fast-paced environment.
- Tech savvy: Enjoy tinkering with the latest technologies and maximizing use of AI assisted tools while keeping security and quality considerations in mind.
Tech stack:
Azure DevOps (Git repos, CI/CD pipelines, PR, app services), LangGraph/Langchain, LangSmith, Github Copilot/Cursor/Claude
Key Qualifications:
- Proven experience in deploying, scaling, integrating, and maintaining GenAI applications using Azure DevOps, Azure App Services, and Azure Functions.
- Strong understanding and experience in software engineering and MLOps best practices.
- Experience with unit testing and regression testing to ensure quality and stability.
- Experience working with full-stack/front-end/back-end engineers to build products. Product-oriented mindset.
- Note: This role is specifically focused on the deployment and integration of GenAI applications. It is not intended for data scientists, dashboard-builders, or those with purely model development experiences.
Other Requirements:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent experience
- At least 2 years of post‑education, non‑internship experience as an ML Engineer or Software Engineer.
- Experience with multi-agent RAG systems
- Strong interest in healthcare, with preferred experience working with healthcare data
Job Type: Full-time
Pay: Competitive pay, benefits, and extremely valuable startup stock options
Schedule: Full Time