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

Education

MSc,MTech,Bachelor of Engineering,BBA,BSc,BTech