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ML Operations Engineer

1 month ago

india EXL Full time
Skills/ Qualifications Required:

Relevant experience in

ML Engineering/ ML Ops role

with an end-to-end understanding of ML based project’s solution design & architecture, development, implementation & deploymentShould fulfill all the standard

MLOps level 2

requirements for CI/CD + CT pipeline automationStrong grasp & hands on experience with production ready scalable code using

SQL (advance)

and

PythonHands-on experience in working on any of the of cloud stacks:

AWS/ Azure/ GCPGood

communication skillsCan work hands-on independently.Bachelor’s degree from

Tier I/II colleges

preferred

Job ResponsibilitiesActively own & manage client deliverables.Design solution architectures and pipelines for ML applications.Create ML prototypes, design ML systems, develop automated ML application pipelines (across data collection, processing, cleaning, transformation etc. aspects) under the constraints of scalability, correctness, and maintainability.Implement model evaluation and model + data validation tools/ techniques such as schema validation, evaluation metrics etc.Develop and deploy fCI/CD based automated ML application pipelines (collection, processing, cleaning, transformation etc.) along with the CT component for continuous feedback loop for re-training.Strong skills in Feature store setup, Pipeline Integration, Automated triggering, Model Continuous Delivery, Model Serving (via APIs) & Model MonitoringResponsible for productionizing and making the models available as APIs / micro services.Promote a practice of unifying system development (Dev) and system operations (Ops)Ensure output’s thorough quality check & provide analytics driven insights and next steps.To perform statistical analysis and fine-tune models using test results.Understand data and different platforms used by the client.Actively contribute towards problem solving & mentor juniors in the team