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Senior Machine Learning Engineer

Altis Labs

Altis Labs

Software Engineering
Canada
Posted on Saturday, November 11, 2023

About Altis Labs

Altis Labs is the computational imaging company advancing precision medicine with AI. We believe that medical imaging is the richest data modality to generate clinical insight. Scientists use our AI-powered software platform, Nota, to accelerate clinical research by more accurately measuring the effect of novel treatments. Trained on over 222 million images with associated clinical information, our deep learning models hosted on Nota predict clinically meaningful outcomes. Legacy data interpretation methods have confined scientists to slow, risky, and expensive drug development requiring more than $2 billion and 10 years to get a new treatment to patients in need.

Our multi-disciplinary team of data scientists, engineers, clinicians, and business operators is on a mission to help get the most effective treatment to patients sooner.

Founded in 2019, Altis is a venture-backed company headquartered in Toronto. We are actively growing our team in Canada and the US across functional areas.

About the Position

Altis is recruiting an experienced Lead MLOps engineer with an entrepreneurial and product-focused mindset. You will develop our cloud-based infrastructure from the ground up, creating bespoke infrastructure and ML pipelines for our growing team and customers. We're looking for someone who is serious about building and is comfortable wearing many hats as a player & coach.

This is a full-time position with the option of working remotely or on a hybrid basis at our office in Toronto. We expect responsibilities will be dynamic and expand as we strive to meet our team’s and clients’ needs.

Responsibilities & Expectations:

  • Design and maintain scalable cloud-based infrastructure for model training and deployment (i.e. deep learning, computer vision)
  • Coach and work with the ML team to operationalize ML solutions and make training/inference infrastructure decisions
  • Create tools, best practices, and automation to reduce time-to-market for ML solutions
  • Ensure solutions are developed according to approved standards and guidelines
  • Collaborate with data scientists, software developers, clinicians and other members of the Altis team to deploy production-scale solutions
  • Troubleshoot and resolve issues with deployed ML models, and provide guidance for improvements

Qualifications:

  • 5+ years of experience developing software in a production environment
  • 3+ years of experience deploying ML solutions including containerization, resource allocation and model management (e.g. Kubeflow, MLFlow, W&B, Argo)
  • 3+ years of experience in cloud architecture design, security, deployment, and related software development
  • Experience with data processing and storage technologies, such as SQL, NoSQL, Hadoop, and Spark
  • Experience handling large imaging data
  • Experience with cloud platforms, such as AWS, Azure, or Google Cloud Platform, and their respective ML services
  • Familiarity with containerization and orchestration tools, such as Docker, Kubernetes, or OpenShift
  • Experience with CI/CD tools and practices, such as Jenkins, GitLab, or CircleCI
  • Advanced degree in computer science, math, statistics, engineering or a related degree
  • Strong programing skills in languages including Python
  • Strong team collaborator
  • Strong written and verbal communication skills in English

Nice to have:

  • Knowledge of state-of-the-art machine learning technologies
  • Knowledge of deep learning architectures including convolution neural networks, recurrent neural network and GANs
  • Familiarity with ML interpretability and explainability techniques
  • Contributions to open-source machine learning or MLOps projects
  • Certifications in cloud platforms, data engineering, or machine learning
  • Past experience in the medical domain

Benefits:

  • Competitive pay and equity compensation
  • Competitive medical, vision, and dental insurance coverage
  • 4 weeks of vacation per year