Senior Machine Learning Engineer

3 weeks ago

Burnaby, British Columbia, Canada Altea Healthcare Full time

Senior Machine Learning Engineer, MLOps

ALTEA Healthcare is a leading healthcare organization committed to revolutionizing the delivery of outpatient/post-acute care. We are seeking an experienced Machine Learning Engineer to join our team. The ideal candidate will have a strong background in deploying scalable ML models, including predictive/classification and NLP/NLU models. As an important member of the AI team, this person will contribute significantly to designing, implementing, and deploying various AI/ML product features to improve care delivery and quality for post-acute patients.

Responsibilities:

  • Develop and deploy production-ready ML models, with a focus on scalability and monitoring across a broad range of applications within healthcare
  • Write efficient, maintainable, and scalable Python code
  • Collaborate with machine learning scientists and data engineers to translate prototype code to production-ready code
  • Set up and maintain end-to-end pipelines including data ingress, egress, model inference, and model retraining
  • Build high-performance deployment architectures and model monitoring systems
  • Incorporate feedback from cross-functional teams and refine the ML-driven applications through quick iteration cycles
  • Maintain best practices of MLOps practices within the healthcare industry
  • Document the system architecture, design decisions, and codebase to facilitate future maintenance and enhancements.

Key Responsibilities and Qualifications:

  • Proven experience in deploying, scaling, integrating, and maintaining generative AI applications.
  • Strong expertise in unit testing and regression testing to ensure quality and stability.
  • Preferred: Experience working with Azure DevOps, Azure App Services, and Azure Functions.
  • Preferred: Experience with fine-tuning and pre-training language models and embedding models.
  • Note: This role is specifically focused on the deployment and integration of generative AI applications. It is not intended for data scientists, individuals primarily focused on building dashboards, or those with experience limited to traditional ML models and model development.

Other Requirements:

  • Bachelor's or Master's degree in Engineering, Computer Science, or equivalent experience
  • At least 4-5 years of relevant experience as an MLOps Engineer
  • 4-5+ years of experience doing MLOps, model monitoring, drift detection, and model retraining
  • Azure Machine Learning Studio
  • Experience with transformer-based models and NLP, preferably in a healthcare context
  • Extensive experience with TensorFlow or PyTorch, and familiarity with HuggingFace
  • Track record of fine-tuning, running large-scale training jobs, and managing model servers like vLLM, TGI, or TorchServe
  • Strong proficiency in LangChain, vectorDB and cloud platforms (Azure), model experimentation tools like MLflow, and monitoring tools like Grafana/Splunk, and CI/CD like airflow, gitlab, and Big Data management like Spark, Kafka
  • Ability to work independently and collaboratively, manage priorities, and deliver high-quality results within project timelines

Job Type: Full-time

Pay: Competitive pay, benefits, and extremely valuable startup stock options

Schedule: Full Time

  • Work Location: Onsite in Burnaby

Benefits:

  • 401(k)
  • Dental insurance
  • Health insurance
  • Vision insurance

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