Devops lead

Lead DevOps/MLOps Engineer for one of our our portfolio companies.

Job Description:

As a Lead DevOps/MLOps Engineer, you'll spearhead the architectural planning and

deployment of our AI-powered security solutions. You'll collaborate closely with machine

learning engineers, software developers, and product managers to facilitate an agile, reliable,

and efficient development environment.

Responsibilities:

Oversee the deployment and orchestration of containerized AI/ML models on Kubernetes in a

cloud environment, specifically AWS.

● Design and implement robust CI/CD pipelines, with particular emphasis on automating

testing and deployment steps.

● Work with developers to scale and optimize the use of GPUs for machine learning

workloads across all environments.

● Collaborate with machine learning engineers to integrate cutting-edge techniques and

models into a production environment.

● Monitor system performance, ensuring uptime, scalability, and effective resource

utilization.

● Manage infrastructure as code through tools like Terraform or CloudFormation.

● Work closely with the product manager and engineering team to prioritize and execute

feature deployments and system improvements.

Requirements:

● 10+ years of experience in software engineering, with at least 5 years focused on

DevOps/MLOps roles.

● Deep expertise in container orchestration technologies like Kubernetes.

● Proficiency in AWS services, especially those related to machine learning and container

management (EKS, ECS etc.).

● Extensive experience with CI/CD tools like Azure DevOps, GitLab CI, or similar.

● Strong understanding of network protocols, security practices, and system monitoring in

a cloud environment.

● Hands-on experience with GPU-based computing and optimization for machine learning

models.

● Excellent problem-solving skills and ability to debug complex systems.

● Strong communication skills and the ability to work effectively in a multidisciplinary team.

● Willingness to keep up with the latest trends in DevOps, cloud computing, and machine

learning operations.