Foundry Digital is hiring a
MLOps Engineer

Summary

Foundry is seeking a MLOps Engineer with 3-6 years of experience to manage the deployment, monitoring, and lifecycle of machine learning models. The ideal candidate will have hands-on experience with MLOps tools, DevOps methodologies, and infrastructure technologies. At Foundry, you'll work in a fast-paced environment with competitive compensation, unlimited PTO, professional development budget, outstanding health insurance, life insurance, short-term & long-term disability coverage (not available for India positions), 401K plan (Bermuda: Private pension plan with company contribution, not available for India positions), flexible spending programs (not available for Bermuda/India positions), and paid parental leave.

Requirements

• 3-6 years of experience in MLOps, DevOps, or a related role with a strong focus on machine learning model deployment and infrastructure
• Experience with MLOps frameworks and tools such as MLflow, Kubeflow, or similar
• Experience with DevOps practices and tools, including Terraform for infrastructure as code (IaC), Ansible for configuration management, Docker for containerization, and Kubernetes for
• Strong understanding of infrastructure components and architecture, including networking, storage, and compute resources
• Experience with cloud services (AWS, Azure, GCP) and cloud-native tools for managing infrastructure and applications
• Proficiency with CI/CD tools such as Jenkins, GitLab CI, or
• Python for scripting, automation, and integrating machine learning models into production environments
• Experience with monitoring tools such as Prometheus, Grafana, ELK Stack, or similar for tracking system health and performance
• Experience with version control systems, particularly

Responsibilities

• Design and implement MLOps pipelines to automate and streamline the deployment, monitoring, and management of machine learning models
• Manage and optimize infrastructure using Terraform and cloud platforms (e.g., AWS, Azure, GCP) to support machine learning workloads
• Develop and maintain CI/CD pipelines tailored for machine learning
• Use Docker for containerizing machine learning applications and Kubernetes for orchestrating and managing containerized
• Implement monitoring solutions for machine learning models and infrastructure
• Work closely with data scientists to understand model requirements and deployment needs
• Maintain thorough documentation for MLOps workflows, infrastructure setups, and deployment

Preferred Qualifications

• Bachelor’s Degree. in Computer Science, Engineering, Data Science, or a related
• Certifications:. Relevant certifications in cloud platforms (e.g., AWS Certified DevOps Engineer) and Kubernetes

Benefits

• Competitive base salary, potential bonus and incentive compensation
• Unlimited PTO / Flexible time off - work with your manager to take time off when you need it
• Professional development budget with flexibility for personal and professional growth
• Outstanding health insurance for employee, partner and dependents
• Life insurance
• Short-term & long-term disability coverage (Not available for India positions)
• 401K plan with company contribution (Bermuda: Private pension plan with company contribution, Not available for India positions)
• Flexible spending programs for medical and dependent care (Not available for Bermuda/India positions)
• Paid parental leave