Machine Learning Ops Engineer

Job Profile Summary

We are seeking a highly skilled and motivated senior MLOps Engineer with experience in Infrastructure as Code (IaC) automation to join our team. The ideal candidate will have a strong background in both software engineering and machine learning, as well as experience building and maintaining large-scale ML models in production. The engineer would also be responsible for building and managing the infrastructure on cloud (AWS or Azure) to deploy ML models in production in conformance with organization's security and compliance needs.

Essential Functions

• Design and implement CI/CD pipelines for ML models, ensuring high availability and low latency

• Build and maintain data pipelines that support ML models

• Monitor model performance and quality in production, and implement mechanisms to detect and prevent model drift

• Collaborate with data scientists to support the development and deployment of new ML models

• Develop and maintain software tools and infrastructure to support the MLOps process

• Automate the deployment and scaling of ML models, and ensure that they are secure and comply with relevant regulations

• Act as a technical advisor to other teams, providing guidance on MLOps best practices and solutions

• Design, implement and maintain IaC automation scripts, using tools such as Terraform, Ansible, or Puppet

Job Complexities

• Competent to work at the highest technical level of all phases of MLOps activities.

• Uses skills as a seasoned, experienced professional with a full understanding of industry

practices and established policies and procedures.

• Troubleshoots a wide variety of complex problems and identifies solutions within broad

applications and functional expertise.

• Regularly provides input to define and implement conceptual issues.

• Foster and maintain good relationships with customers and IT colleagues to meet expected

customer service levels.

• Problem-solve and think laterally as part of a team, or individually, to meet the needs of the project

Supervision Received or Extended

• Works independently under broad supervision.

• Uses expertise of other team members and leverages a wide range of additional resources

to explore/implement complex customized applications as a solution.

Impact

• Erroneous decisions will have an impact on the overall success of department operations.

Knowledge and Skills/Technology Used

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field with 5+ years of relevant experience

• Strong knowledge of software engineering principles and experience with at least one programming language (e.g., Python, Java, Scala, etc.)

• Strong understanding of ML models and algorithms

• Experience with cloud computing platforms, such as AWS, GCP, or Azure

• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes)

• Experience with IaC automation tools and scripts (e.g., Terraform, Ansible, Puppet, etc.)

• Experience with Snowflake and cloud based data pipelines

• MLaaS platforms such as Azure ML and AWS Sagemaker

• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams

• Proficient in version control and DevOps tools such as GitLab/GitHub/Azure DevOps

• Strong organizational or Project Management skills

• Strong written and verbal communication skills

Typical Education

• Bachelor's Degree in Computer Science, Software Engineering, or a related field

• Master's degree preferred

Typical Range of Experience

• 5-7 years of related work experience in DevOps and MLOps, building machine leaning platform solutions