MLOPS Engineer

4 weeks ago

Gurugram, India EXL Full time

Experience- 10 Yrs


Relevant experience in ML Engineering/ ML Ops role with an end-to-end understanding of ML based project’s solution designing, development, implementation & deployment

Should fulfill all the standard MLOps level 2 requirements for CI/CD + CT pipeline automation

Strong grasp & hands on experience with production ready scalable code using SQL (advance) and Python, along with an in-depth knowledge of Machine Learning concepts

Hands-on experience in working on AWS cloud stack

Working experience Sagemaker, EC2, S3, EMR, Lambda Functions, Cloudwatch, etc.

At least 2 year of experience in orchestrating ML Jobs on Airflow, Step Functions, Model registry etc.

Knowledge of Jenkins for CI/CD tool

Good communication skills

Experience with version control tools such as MLFlow, DVC, Pachyderm etc.

Good to have: Experience with Google Analytics data, PySpark

Bachelor’s degree from Tier I/II colleges preferred (Post Graduation – Good to have, not mandatory)

Job Responsibilities

  • Actively own & manage client deliverables.
  • Collaborate with data scientists, data engineers, and other MLOps Engineers to solve complex problems and create unique solutions for MLOps
  • Create ML prototypes, design ML systems, research, and implement ML algorithms, and develop machine learning applications in accordance with client needs.
  • Should have implementation experience of model evaluation and model + data validation tools/ techniques such as schema validation, valuation metrics etc.
  • Responsible for developing and deploying CI/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 Monitoring
  • 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
  • Can work hands-on independently

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