Its fun to work in a company where people truly BELIEVE in what they are doing!
Brief about the Team & Fractal:
Fractal Analytics is Leading Fortune 500 companies leverage Big Data, analytics and technology to drive smarter, faster and more accurate decisions in every aspect of their business.
Fortune 500 companies recognize analytics is a competitive advantage to understand s and make better decisions. We deliver insight, innovation and impact to them through predictive analytics and visual storytelling.
RESPONSIBILITIES:
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
LEADERSHIP CHARACTERISTICS
Understanding the Business
Knows the business and the mission-critical technical and functional skills needed to do the job; understands various types of business propositions and understands how businesses operate in general; learns new methods and technologies easily.
Customer Focus
Promises relentless motivation to meet and exceed the needs and expectations of the customers in all aspects.
Innovation Led Transformation
Understand the importance of vision and of working with people to deliver success. Encourage, inspire, and motivate to drive innovation and create change
Making complex decisions
Can solve even the toughest and most complex of problems; great at gleaning meaning from whatever data is available; is a quick study of the new and different; adds personal wisdom and experience to come to the best conclusion and solution, given the situation; uses multiple problem-solving tools and techniques.
Managing diverse relationships
Relates well to a wide variety of diverse styles, types, and classes; open to differences; effective up, down, sideways, inside, and outside; builds diverse networks; quick to find common ground; treats differences fairly and equitably; treats everyone as a preferred customer.
EDUCATION:
B.E/B.Tech/M.Tech in Computer Science or related technical degree OR Equivalent
If you like wild growth and working with happy, enthusiastic over-achievers, youll enjoy your career with us!
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