MLOPS Engineer

What Working at Hexaware offers:

Hexaware is a dynamic and innovative IT organization committed to delivering cutting-edge solutions to our clients worldwide. We pride ourselves on fostering a collaborative and inclusive work environment where every team member is valued and empowered to succeed.

Hexaware provides access to a vast array of tools that enhance, revolutionize, and advance professional profile. We complete the circle with excellent growth opportunities, chances to collaborate with highly visible customers, chances to work alongside bright brains, and the perfect work-life balance.

With an ever-expanding portfolio of capabilities, we delve deep into and identify the source of our motivation. Although technology is at the core of our solutions, it is still the people and their passion that fuel Hexaware’s commitment towards creating smiles.

“At Hexaware we encourage to challenge oneself to achieve full potential and propel growth. We trust and empower to disrupt the status quo and innovate for a better future. We encourage an open and inspiring culture that fosters learning and brings talented, passionate, and caring people together.”

We are always interested in, and want to support, the professional and personal you. We offer a wide array of programs to help expand skills and supercharge careers. We help discover passion—the driving force that makes one smile and innovate, create, and make a difference every day.

The Hexaware Advantage: Your Workplace Benefits

• Excellent Health benefits with low-cost employee premium.
• Wide range of voluntary benefits such as Legal, Identity theft and Critical Care Coverage
• Unlimited training and upskilling opportunities through Udemy and Hexavarsity

Role: MLOPS Engineer

Location: Reston, VA(day one onsite)

Experience: 10 years

Work Mode: Onsite

Salary Range: Market Rate

Job Key Responsibilities:

Job description:

MLOPS Engineer

• MLOPS (Machine Learning Operations): The MLOPS Engineer will design and build scalable machine learning infrastructure, ensuring smooth deployment, monitoring, and lifecycle management of ML models.
• Responsibilities include automating workflows, enabling continuous integration/continuous deployment (CI/CD) pipelines.
• Develop and Maintain ML Infrastructure: Build and maintain ML pipelines that support model training, testing, deployment, and monitoring.
• Model Deployment: Implement efficient processes for deploying ML models in production environments, such as cloud platforms or on-premises infrastructure.
• Set up CI/CD pipelines for continuous integration and delivery of ML models. Automation and Scaling: Automate model retraining, validation, and performance monitoring processes.
• Collaboration with Data Scientists: Work closely with data scientists to streamline the model development lifecycle and ensure models can easily be transitioned to production.
• Monitoring and Optimization: Monitor ML models in production for accuracy and performance and troubleshoot any deployment or scaling issues.
• Infrastructure as Code (IaC): Develop infrastructure as code to manage cloud resources for ML workloads.
• Versioning and Experimentation Tracking: Implement model versioning, experiment tracking, and reproducibility techniques.
• Security and Compliance: Ensure models comply with organizational security standards and regulatory guidelines.
• Containerization: Hands-on experience with Docker, Kubernetes, or other container orchestration systems.
• CI/CD Tools: Knowledge of Jenkins, GitLab, CircleCI, or other CI/CD tools for automation.
• Data Pipelines: Experience orchestration tools for managing data pipelines.
• Version Control: Familiarity with Git for code versioning.
• DevOps Experience: Basic understanding of DevOps tools and practices (e.g., Terraform)
• 8 years of experience on Python and AWS Services using ML Models Implementation to Production

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