MLE/MLOps consultant

Job Description:

• Seeking smart, self-driven, high-energy professionals with exceptional communication skills, strong intellectual curiosity, and a genuine passion for technology in the Machine Learning space
• Our analysts bring deep domain expertise in one or more areas within the Retail and CPG domain, strong business acumen, and excellent soft skills, along with exposure to technology
• Technical Skills
• Must Have Skills
• MLOps implementation and support experience
• Proficiency in Python programming (expert level), with 4–5 years of experience
• DevOps working knowledge with implementation experience on at least 1 or 2 projects
• Hands-on MS Azure cloud knowledge
• Operations experience, if any
• List of required Azure services for deployment, including Azure Databricks and Azure DevOps setup
• Strong command of coding standards (e.g., flake8)
• Automation technology and process improvement for deployed projects
• Agile training to manage team efforts and track progress through JIRA
• Nice to have Skills
• Understanding of at least one domain (e.g., Retail, Supply Chain, Logistics, Manufacturing)
• Soft Skills
• Strong verbal and written communication skills with the ability to work effectively in a team
• Strong customer focus, ownership, urgency, and drive
• Ability to manage multiple competing priorities in a fast-paced environment
• Ability to work well with team members to maintain high credibility
• Work Experience
• 3–5 years of experience in Machine Learning, Azure, and MLOps

Key Responsibilities:

• Understand business requirements and translate them into appropriate technical requirements
• Own the successful delivery of MLOps solutions and services in client consulting environments
• Identify key business problems, develop high-level solution approaches, determine the required data, analyze and draw conclusions, and present findings to clients
• Support clients with operationalization metrics to track ML model performance
• Assist the team with ML pipelines from creation through execution
• Help teams debug pipeline issues and failures
• Capture and work on operationalization requirements for ML models received from data scientists
• Coordinate with business stakeholders by providing status updates on development progress and issue resolution
• Set up standards related to coding, pipelines, and documentation
• Conduct 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 a consistent academic track record
• Bachelor’s degree in a quantitative discipline, e
• g
• Operation Research, Statistics, Mathematics, or significant relevant coursework with a consistent academic track record
• Additional Academic Qualification (good to have)
• Master’s in any area related to Science, Operation Research, Mathematics, and Statistics with a consistent academic track record
• PhD in any stream

Additional Responsibilities:

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

Preferred Skills:

Technology->AI-AI Engineering->MLOps