Lead Data Scientist GenAI & MLOps Immediate Joiner

Role & responsibilities

• Work within the AI/ML Platform Enablement team supporting eCommerce Analytics.
• Collaborate with Data Scientists to develop and maintain production models.
• Deploy and configure Kubernetes components for production, including API Gateway, Ingress, Model Serving, Logging, Monitoring, and Cron Jobs.
• Optimize model deployment processes for faster builds and efficient workflows.
• Lead technical projects across platforms and contribute to platform architecture.
• Drive operational excellence in AI/ML, including resource efficiency, system optimization, and capacity forecasting.
• Design and implement scalable architectures for AI/ML performance and resiliency.
• Develop capability roadmaps and transition plans for next-gen AI/ML enablement technologies.

Preferred candidate profile

Required Skills & Tools (Hands-on Experience Required):

• Strong expertise in GenAI applications and NLP models.
• Experience in LLM-based application development.
• Hands-on experience in MLOps pipeline design and development.
• Knowledge of parameterized and non-parameterized algorithms in Data Science.
• Experience in ML pipeline development using containerized components.
• Worked on at least one Kubernetes cloud offering (EKS, GKE, AKS) or on-prem Kubernetes.
• Proficiency in Python, PySpark, PyTorch, Langchain, Docker, and Kubeflow.
• Familiarity with observability tools like Splunk, Prometheus, and Grafana for system diagnostics.
• Experience in Web Development.

Education & Experience:

• 6+ years of relevant experience in AI/ML, Data Science, and MLOps in cloud-based distributed environments.
• Graduate degree in a quantitative field such as Computer Science, Engineering, Mathematics, or Operations Research.
• Proven track record in solving large-scale enterprise data operations challenges requiring cross-functional collaboration.

Note: Candidates should be available for immediate joining.