At CoMind, we are developing a non-invasive neuromonitoring technology that will result in a new era of clinical brain monitoring. In joining us, you will be helping to create cutting-edge technologies that will improve how we diagnose and treat brain disorders, ultimately improving and saving the lives of patients across the world.
The Role
CoMind is seeking a skilled DevOps Engineer to join our dynamic Research Data Science team to lead the orchestration of a robust ML training pipeline in AWS. This role is critical to enabling the scalable training and testing of a range of ML models on large volumes of a totally new form of clinical neuromonitoring data.
Responsibilities:
* Architect and implement a scalable solution to support the Research Data Science Team in running a large number of assorted machine learning pipelines, including model training, evaluation, and inference
* Create a CI/CD pipeline for building containers from in-house Python packages, running integration tests, and publishing to AWS ECR
* Set up ECS or AWS Batch Tasks to run containers stored in AWS ECR
* Establish a robust configuration management system to store, version, and retrieve configurations associated with multiple machine learning workflows
* Implement robust error handling and monitoring solutions to ensure timely debugging across the pipeline with centralised logging and error reporting
* Implement cost monitoring solutions to track and manage compute costs across different runs, building dashboards to provide insights into resource usage and cost optimization
* Ensure security and data protection are integrated into the pipelines by applying AWS best practices for security protocols and data management
* Monitor and manage the team's compute resources, including both cloud (AWS) and on-premise GPU nodes, ensuring efficient use and scalability
* Implement Infrastructure as Code (IaC) to set up and manage the pipeline architecture, using Terraform, AWS CloudFormation, or similar tools.
Skills & Experience:
* Git or Bitbucket for version control, including experience with managing versioned infrastructure-as-code (IaC) repositories
* CI/CD pipelines for automating workflows, including experience with integration testing and containerization pipelines
* Experience managing and orchestrating complex cloud workflows (e.g., ECS Tasks, AWS Batch), with a focus on event-driven and parallel processing
* Infrastructure as Code (IaC) experience (e.g., Terraform, AWS CloudFormation) for creating, maintaining, and scaling cloud infrastructure
* Docker for containerization, including experience with containerizing machine learning workflows and publishing containers to repositories like AWS ECR.
Benefits:
* Company equity plan
* Company pension scheme
* Private medical, dental and vision insurance
* Group life assurance
* Comprehensive mental health support and resources
* Unlimited holiday allowance (+ bank holidays)
* Hybrid working (3 days in-office)
* Quarterly work-from-anywhere policy
* Weekly lunches
* Breakfast and snacks provided.
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