Machine Learning Operations Specialist

2 weeks ago

Hyderabad, Telangana, India People Prime World Wide Full time

Job Description

Job Title : Senior MLOps Specialist AWS Cloud.

Location : Hyderabad.

Type : ValueMomentum Advanced Analytics Center

ValueMomentum has strategically established an Advanced Analytics Center to strengthen AI and analytics capabilities in the Property & Casualty (P&C) Insurance sector.

This unit focuses on revolutionizing insurance with innovative AI solutions, fostering reusability, experimentation, and capability development.

Our environment is dynamic, collaborative, and innovation-driven, comprising data scientists, analysts, and consultants.

The Advanced Analytics team delivers cutting-edge AI/analytics solutions across the P&C value chain Product/Underwriting, Claims, Distribution, and Enterprise IT.


Job Summary :

We are seeking an experienced Sr. MLOps Specialist with deep expertise in AWS services and machine learning deployment best practices.

The role involves designing, building, and maintaining scalable, secure, and automated ML pipelines.

You will bridge the gap between data science and engineering teams, ensuring ML models are production-ready and efficiently managed throughout their Responsibilities :

Design & Implement MLOps Pipelines.

- Build and maintain robust CI/CD pipelines for ML using Amazon SageMaker Pipelines, CodePipeline, Step Functions.

- Automate model training, evaluation, deployment, and monitoring.

- Infrastructure & Cloud Management.

- Use Infrastructure-as-Code (IaC) tools (CloudFormation, Terraform, CDK) for reproducible environments.

- Architect scalable ML infrastructure with AWS services (S3, Lambda, ECR, EC2, SageMaker).

Monitoring, Logging & Observability.

- Implement model and data monitoring with SageMaker Model Monitor, CloudWatch, or third-party tools.

- Set up logging, alerts, and dashboards for model health and performance.

Governance & Compliance.

- Manage model registries, lineage tracking, and audit logging.

- Ensure version control and approval workflows for ML assets.

Collaboration & Enablement.

- Partner with data scientists, ML engineers, and DevOps teams to integrate ML workflows.

- Educate and mentor teams on MLOps best practices and AWS ML Skills & Qualifications :

- 8+ years experience in DataOps, DevOps, or ML Engineering with focus on cloud-based ML pipelines.

Strong expertise with AWS services, including :

- Amazon SageMaker (training, deployment, Pipelines, Model Monitor).

- S3, Lambda, Step Functions, CodePipeline, ECR, CloudWatch.

- Proficiency in Python, Bash, scripting for automation.

- Hands-on with CI/CD tools (Jenkins, GitHub Actions, CodeBuild).

- Experience with Docker and container orchestration (ECS, EKS optional).

- Solid understanding of ML lifecycle (feature engineering, training, deployment, monitoring).

- Familiarity with model tracking tools (MLflow, DVC, SageMaker Model Registry).

- Strong communication and collaboration skills.

(ref:hirist.tech)

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