MLOps Engineer

5 days ago

bangalore, India C5i Full time
C5i
C5i is a pure-play AI & Analytics provider that combines the power of human perspective with AI technology to deliver trustworthy intelligence. The company drives value through a comprehensive solution set, integrating multifunctional teams that have technical and business domain expertise with a robust suite of products, solutions, and accelerators tailored for various horizontal and industry-specific use cases. At the core, C5i’s focus is to deliver business impact at speed and scale by driving adoption of AI-assisted decision-making.
C5i caters to some of the world’s largest enterprises, including many Fortune 500 companies. The company’s clients span Technology, Media, and Telecom (TMT), Pharma & Lifesciences, CPG, Retail, Banking, and other sectors. C5i has been recognized by leading industry analysts like Gartner and Forrester for its Analytics and AI capabilities and proprietary AI-based platforms.
Global offices
United States | Canada | United Kingdom | United Arab of Emirates| India
Job Responsibilities
Model Deployment:
Deploy machine learning models in production environments on cloud platforms such as Azure and AWS.
Work closely with data scientists and software engineers to integrate models into existing systems.
Infrastructure Management:
Set up and maintain infrastructure for machine learning model deployment.
Ensure smooth integration of ML workflows into CI/CD pipelines.
Monitoring and Maintenance:
Implement and manage robust monitoring solutions to track model performance, data drift, and other relevant metrics.
Proactively identify and address issues related to model degradation or system failures.
Cloud Expertise:
Demonstrate expertise in cloud platforms, particularly Azure and/or AWS, for deploying and managing machine learning services.
Automation and Scripting:
Develop automation scripts and tools to streamline deployment processes and enhance efficiency.
Implement infrastructure as code (IaC) practices for reproducibility and scalability.
Requirements & Qualifications:
Experience: 5-8 years of hands-on experience in deploying and monitoring machine learning models.
Basic understanding of ML and data science/modeling aspects.
Technical Skills:
Proficiency in cloud platforms, especially Azure and/or AWS.
Experience with open-source tools for MLOps, such as Kubernetes, Docker, and Apache Airflow and developing and streamlining workflows, building scalable pipelines, etc.
Ensuring successful model development, testing, optimization, scaling, monitoring/observability, and governance.
Continuous integration and continuous deployment (CI/CD).
Knowledge of best practices and processes to promote reproducibility in a centralized manner (cloud/hybrid infrastructure and environment).
Strong scripting skills (e.g., Python) for automation and tool development.
Problem-Solving :
Strong problem-solving skills with a focus on finding efficient and scalable solutions.
Ability to learn new tools on the go and developing best practices is mandatory.

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