As MLOps Engineer, you will work collaboratively with Data Scientists and Data engineers to deploy and operate advanced analytics machine learning models. You ll help automate and streamline Model development and Model operations. You ll build and maintain tools for deployment, monitoring, and operations. You ll also troubleshoot and resolve issues in development, testing, and production environments.
Enable Model tracking, model experimentation, Model automation Develop scalable ML pipelines
Develop MLOps components in Machine learning development life cycle using Model Repository (either of) : MLFlow, Kubeflow Model Registry
Machine Learning Services (either of) : Kubeflow, DataRobot, HopsWorks, Dataiku or any relevant ML E2E PaaS / SaaS
Work across all phases of Model development life cycle to build MLOPS components
Build the knowledge base required to deliver increasingly complex MLOPS projects on the Cloud(AWS, Azure, GCP) / On Prem Be an integral part of client business development and delivery engagements across multiple domains.
Technical Leadership :
As the MLops leader, S / he will support client projects, lead solution design, and contribute to the overall MLOps engineering using on-premise (open-source) or cloud-based (GCP / Azure / AWS) architectures
Looking for candidate with 10-14 Years of experience candidates ideally
Act as a subject matter expert in machine-learning model deployment and MLops pipelines - strong understanding of Machine-learning model building lifecycle, deployment, monitoring and production
Research and evangelize the use of the data-science and engineering solutions for strategic decision-making
Articulate business value and benefits of the technological solution to senior business and technology partners
Research, design and implement leading-edge MLops architecture patterns to solve hard problems for the clients
Bring data-science engineering thinking to win large AI led digital transformation deals
Thought Leadership :
Lead and energize the teams and clients by providing thought leadership in enterprise-grade machine-learning operations and modern cloud adoption patterns
Act as a Trusted Advisor and build trust with customers through strategic thought, exceptional execution, and technical depth and expertise to help them execute large scale data science / ML projects
Building High Performance Culture :
Help build and retain high performance (CoE) teams
Develop people and teams to build the knowledge base required to deliver increasingly complex technology projects
Foster a work environment that is innovative and agile. Hire and retain the best industry talent with right talent management planning.
Drive continuous systems improvement, including general administration and management.
Help build a culture that is open, transparent, and risk-taking
Skills Required
Gcp, MLops, Azure, Aws
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Lead Architect • Pune, Mumbai, Chennai
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