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.

Below, you will find a complete breakdown of everything required of potential candidates, as well as how to apply Good luck.The RoleCoMind 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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