Job Description

The ideal candidate for this role should possess a strong blend of MLOps and ML engineering skills.




Technological Stack: Python, AWS services (ECS, Batch Compute, S3, Timestream, IAM, CloudWatch, Athena), Airflow for orchestration, MLflow for model versioning, GitLab CI, and eventually, AWS SageMaker pipelines.


Data Engineering Skills: Expertise in pipeline monitoring, including getting data from Bulk CDM, investigating query issues, and sending output data to ALTO.


ML Engineering Skills: Experience with debugging forecast and clustering models, setting up and automating CI/CD for ML workflows, developing and deploying end-to-end ML pipelines (data preparation, training, validation, deployment), and a strong background in ML frameworks like LightGBM.


MLOps Engineer to handle the tickets, and Data Engineering tickets/development

About Virtusa

Teamwork, quality of life, professional and personal development: values that Virtusa is proud to embody. When you join us, you join a team of 27,000 people globally that cares about your growth -- one that seeks to provide you with exciting projects, opportunities and work with state of the art technologies throughout your career with us.



Great minds, great potential: it all comes together at Virtusa. We value collaboration and the team environment of our company, and seek to provide great minds with a dynamic place to nurture new ideas and foster excellence.



Virtusa was founded on principles of equal opportunity for all, and so does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need.