ML Operations Engineer

0 years

0 Lacs

Posted:2 days ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Full Time

Job Description

Skills/ Qualifications Required:


ML Engineering/ ML Ops role

MLOps level 2

SQL (advance)

AWS/ Azure/ GCP

communication skills

  • Can work hands-on independently.

Tier I/II colleges



Job Responsibilities

  • Actively 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 Monitoring

Responsible 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

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