MLOps Engineer

Job Title:MLOpsEngineer

About Us:

Inovalonis a leading healthcare technology company dedicated to revolutionizing the healthcare industry through innovative AI and machine learning solutions. Our mission is toleveragecutting-edgetechnology to improve health outcomes and streamline healthcare processes.

Role overview

As anMLOpsEngineer, you will design, build, andoperatethe infrastructure and tooling that power end-to-end ML workflows on AWS, including SageMaker, Bedrock, and Snowflake Cortex. You will partner closely with data scientists, ML engineers, and platform teams to ensure models are reliable, secure, and scalable in production.

Key responsibilities

• Design, implement, andmaintainCI/CD pipelines for ML models and data workflows using AWS-native services and infrastructure-as-code.

• Operationalize models built on SageMaker, Bedrock, and Snowflake Cortex, including feature pipelines, training, batch/real-time inference, and monitoring.

• Build and manage data pipelines and feature stores using services such as AWS Glue, Lambda, Step Functions, and Snowflake.

• Implement observability for ML systems (logging, metrics, tracing, drift/quality monitoring) andestablishSLOs/SLAs forproductionML services.

• Automate environment provisioning, configuration, and dependency management across dev, test, and production.

• Partner with security and compliance teams to ensure ML workloads meet healthcare, privacy, and regulatory standards (e.g., HIPAA).

• Collaborate with ML engineers and data scientists toproductionizenotebooks and prototypes into robust, maintainable services.

• Contribute to best practices, standards, and documentation for MLplatformand operations across the organization.

Qualifications

• Bachelor's orMaster's degree in Computer Science, Engineering, Mathematics, ora relatedfield.

• 8+ years of experience in software engineering, data engineering, or ML engineering with at least 4+ years focused on MLOps or ML platform work.

• Strongproficiencywith Python and experience integrating ML libraries or frameworks (e.g., scikit-learn, TensorFlow,PyTorch) into production workflows.

• Hands-onexpertisewith AWS services relevant toMLOps: SageMaker, Bedrock, IAM, CloudWatch, ECR, ECS/EKS or Lambda, S3, Step Functions, and Glue.

• Experience with Snowflake (including Snowflake Cortex), SQL, and building secure, performant data pipelines into and out of Snowflake.

• Proficiencywith CI/CD tools (e.g., GitHub Actions, GitLab CI, CodePipeline) and infrastructure-as-code (e.g., Terraform, CloudFormation, CDK).

• Familiarity with containerization and orchestration (Docker, Kubernetes) and event streaming tools (e.g., Kafka) is a plus.

• Knowledge of software engineering best practices, including testing, code reviews, version control, and design for reliability and scalability.

• Experience in regulated domains or with healthcare data standards and regulations is a plus (e.g., HIPAA, FHIR, HL7).

Soft skills and benefits

• Excellent problem-solving and analytical skills with a focus on reliability and automation.

• Strong communicationand collaboration abilities, including working cross-functionally with engineering, data science, and product teams.

• Ability to work independently in a fast-paced environment

• Competitive salary and benefits package.

• Opportunity to work on impactful ML platforms that improve healthcare outcomes.

• Collaborative, innovative environment with professional development and growth opportunities.