Job Description

• Bengaluru, Karnataka, India (On-site)

About:

We are an AI (Artificial Intelligence) Economics research and deployment company, dedicated to discovering and implementing the path to quantitative information commerce. Kunato.Ai's approach to quantitative information commerce paves the way for a new content value-based economy, aligning creators (both humans and AI) and consumers. Our platform optimizes content creation, search, monetization, and consumption, emphasizing credibility, trustworthiness, reputation, and quality. We envision a world where our solutions enhance productivity, education, decision-making, innovation, transparency, and fairness, creating a more equitable and profitable market for all.

Mission Statement:

Our mission is to discern the true value of information and transform the digital content economy. If you are an MLOps Engineer with a passion for innovation and the expertise to efficiently manage and productionize machine learning models, Kunato.AI is the place for you.

Position Overview:

As a ML Ops Engineer at Kunato.AI, you will play a pivotal role in managing and productionizing machine learning models, ensuring their efficiency, performance, and reliability. You will be responsible for a wide range of tasks, from model versioning, writing scalable micro services, deploying services in cloud platform using Kubernetes.

Roles and Responsibilities:

• Manage model training and automated retraining processes to keep models up to date.
• Establish end-to-end model workflows, from onboarding and operations to decommissioning.
• Establish ML Ops CI CD pipeline
• Building Scalable Micro Services to move the ml models to production
• Implement model version tracking and governance for better model management.
• Oversee data archival and version management to maintain data integrity.
• Monitor models and data drift to detect and respond to anomalies.
• Provide best practices and execute proofs of concept (POCs) for automated and efficient model operations at scale.
• Design and develop scalable MLOps frameworks tailored to client requirements.
• Serve as the MLOps expert for the sales team, offering technical design solutions to support RFPs and client needs.

Skillset for the Role:

• Strong Knowledge and Hands on Experience with Python frameworks (Fast Api, Flask, Pandas, NumPy)
• Experience with any of the cloud platform (GCP, AWS, Azure, Digital Ocean)
• Experience in Kubernetes, Docker or equivalent
• Experience in any one of these Airflow, MLflow, Kubeflow
• Basic Knowledge about ML algorithms and frameworks
• Demonstrated ability to design and develop scalable MLOps frameworks.
• Experience in SQL and NoSQL databases

Years of Experience:

• Looking for 1.5 years – 3.5 years of experience in MLOps, data engineering, or related roles.

Notice Period: Immediate/ Serving Notice Period / 1 Month