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.