MLE/MLOps consultant

We are looking for smart, self-driven, high energy people with top notch communication skills, intellectual curiosity and passion for technology in Machine Learning Space. Our analysts have a blend of in-depth domain expertise in one or more areas (in Retail and CPG Domain), strong business acumen and excellent soft skills & Exposure to Technology.

Technical Skills: Must Have Skills:

• MLOps Implementation and Support Experience
• 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
• Operations Experience if any
• List Azure services required for deployment, Azure Data bricks and Azure DevOps Setup
• Well verse in coding standards (flake8 etc)
• Automation, Technology and Process Improvement for the deployed projects
• Agile trained to manage team effort and track through JIRA

Nice to have Skills:

• Understanding of any one of domain (Eg: Retail, Supply chain, Logistics, Manufacturing).

Soft Skills:

• Strong verbal and written communication skills with the ability to work well in a team.
• Strong customer focus, ownership, urgency, and drive.
• Ability to handle multiple, competing priorities in a fast-paced environment.
• Work well with the team members to maintain high credibility.

Work Experience:

• 3-5 years of experience in Machine Learning, Azure and MLOps.

• Understand the requirements from the business and translate it into an appropriate technical requirement.
• 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
• Help team with ML Pipelines from creation to execution
• Guide team to debug on issues with pipeline failures
• Understand and take requirements on Operationalization of ML Models from Data Scientist