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.

Responsibilities

• 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
• Engage with Business / Stakeholders with status update on progress of development and issue fix
• Setup Standards related to Coding, Pipelines and Documentation
• Research on new topics, services and enhancements in Cloud Technologies

Technical requirements

Educational Requirements (any of the following):

• Bachelor of Engineering/Bachelor of Technology in any stream with consistent academic track record.
• Bachelor's degree in a quantitative discipline (e.g., Operation Research, Statistics, Mathematics) or significant relevant coursework with consistent academic track record.

Additional Academic Qualification (good to have):

• Masters in any area related to Science, Operation Research, Mathematics and Statistics with consistent academic track record.
• PhD in any stream.

Additional responsibilities

• Good knowledge on software configuration management systems
• Strong business acumen, strategy and cross-industry thought leadership
• Awareness of latest technologies and Industry trends
• Logical thinking and problem solving skills along with an ability to collaborate
• Two or three industry domain knowledge
• Understanding of the financial processes for various types of projects and the various pricing models available
• Client Interfacing skills
• Knowledge of SDLC and agile methodologies
• Project and Team management

Preferred skills

Technology->AI-AI Engineering->MLOps

Education

MCA,MSc,MTech,Bachelor of Engineering,BE,BSc,BTech