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ML Ops Engineer @ Infobeans

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 ML Ops Engineer

Job Description

Role & responsibilities


  • University Degree in Computer Science, Information Technology, or related field
  • 5+ years of experience in the Machine Learning Operations role
  • Design the data pipelines and engineering infrastructure to support our clients enterprise machine learning systems at scale
  • Take offline models data scientists build and turn them into a real machine learning production system
  • Develop and deploy scalable tools and services for our clients to handle machine learning training and inference
  • Identify and evaluate new technologies to improve performance, maintainability, and reliability of our clients machine learning systems
  • Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
  • Support model development, with an emphasis on auditability, versioning, and data security
  • Facilitate the development and deployment of proof-of-concept machine learning systems
  • Communicate with clients to build requirements and track progress
  • Strong analytic skills related to working with structured, semi structured and unstructured datasets
  • Advanced Machine learning techniques: Decision Trees, Random Forest, Boosting Algorithm, Neural Networks, Deep Learning, Support Vector Machines, Clustering, Bayesian Networks, Reinforcement Learning, Feature Reduction

Job Classification

Industry: IT Services & Consulting
Functional Area / Department: Data Science & Analytics
Role Category: Data Science & Machine Learning
Role: Data Science & Machine Learning - Other
Employement Type: Full time

Contact Details:

Company: Infobeans
Location(s): Chennai

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Keyskills:   Cicd Methodology ML Operations Algorithms ML Workflow Machine Learning Automation

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Infobeans

InfoBeans Systems is a fast growing software development company with offices in Pune and Indore and business development centre in US. We develop customized business applications for large and mid-size organizations in the US. We strongly believe that customer success defines our success. Hence, we...