Machine Learning Engineer Post by Infosys

February 25, 2024
Machine Learning Engineer Post by Infosys

Job Description


  • Responsible for successful delivery of MLOps solutions and services in client consulting environments;
  • Define key business problems to be solved; formulate high level solution approaches and identify data to solve those problems, develop, analyze/draw conclusions and present to client.
  • Assist clients with operationalization metrics to track performance of ML Models
  • Agile trained to manage team effort and track through JIRA
  • High Impact Communication- Assesses the target audience need, prepares and practices a logical flow, answers audience questions appropriately and sticks to timeline.

Technical and Professional Requirements:

  • Technical knowledge- has expertise in cloud technologies, specifically MS Azure, and services with hands on coding to –
  • Python Programming – Expert and Experienced – 4 -5 years
  • DevOps Working knowledge with implementation experience – 1 or 2 projects a minimum
  • Hands-On MS Azure Cloud knowledge
  • Understand and take requirements on Operationalization of ML Models from Data Scientist
  • Help team with ML Pipelines from creation to execution
  • List Azure services required for deployment, Azure Data bricks and Azure DevOps Setup
  • Assist team to coding standards (flake8 etc)
  • Guide team to debug on issues with pipeline failures
  • Engage with Business / Stakeholders with status update on progress of development and issue fix
  • Automation, Technology and Process Improvement for the deployed projects
  • Setup Standards related to Coding, Pipelines and Documentation
  • Adhere to KPI / SLA for Pipeline Run, Execution
  • Research on new topics, services and enhancements in Cloud Technologies

Preferred Skills:

  • Analytics->Machine Learning

Work Experience:

  • 2-5 Years

Additional Responsibilities:

  • Master’s degree in Computer Science Engineering, with Relevant experience in the field of MLOps / Cloud
  • Domain experience in Capital Markets, Banking, Risk and Compliance etc.
  • Exposure to US/ overseas markets is preferred
  • Azure Certified – DP100, AZ/AI900
  • Domain / Technical / Tools Knowledge:
  • Object oriented programming, coding standards, architecture & design patterns, Config management, Package Management, Logging, documentation
  • Experience in Test Driven Development and experience in using Pytest frameworks, git version control, Rest APIs
  • Azure ML best practices in environment management, run time configurations (Azure ML & Databricks clusters), alerts.
  • Experience designing and implementing ML Systems & pipelines, MLOps practices
  • Exposure to event driven orchestration, Online Model deployment
  • Contribute towards establishing best practices in MLOps Systems development
  • Proficiency with data analysis tools (e.g., SQL, R & Python)
  • High level understanding of database concepts/reporting & Data Science concepts
  • Hands on experience in working with client IT/Business teams in gathering business requirement and converting into requirement for development team
  • Experience in managing client relationship and developing business cases for opportunities
  • Azure AZ-900 Certification with Azure Architecture understanding is a plus

Educational Requirements:

  • Bachelor of Engineering 

Service Line:

  • Data & Analytics Unit