Chance to work on financial data for complex retail problems/challenges. Utilize Genai/LLM methods and architectures to build and deploy state-of-the-art forecasting systems.
Requirements
- Experience in productionizing Data Science, ML and Genai Models
- Experience in designing scalable ML/Genai applications incorporating Data Pipelines, Model Training, Inferencing, Versioning and Monitoring.
- Experience in cloud platforms such as GCP and Azure.
- Experience in implementing CI/CD pipelines using Jenkins and Devsecops processes using Code Quality Inspection tools such as SonarQube and Synk.
- Experience in creating Unit, End to End, Functional and Regression Testing Frameworks.
- Experience in Backend development which includes API development using Fast API/Flask, Cache using Redis, Asynchronous Job processing using Celery, and Message Brokers using RabbitMQ/Kafka/Google Pub/Sub.
- Experience containerizing application using Docker and Orchestration using Airflow and Kubernetes.
Responsibilities
- Lead a high-performing team to build Genai, Agentic AI systems.
- Build cross-functional partnerships to drive collaborative success.
- Interface with users to collect requirement and feedback.
- Experience in productionizing Data Science, ML and Genai Models
- Experience in designing scalable ML/Genai applications incorporating Data Pipelines, Model Training, Inferencing, Versioning and Monitoring.
- Experience in implementing CI/CD pipelines using Jenkins and Devsecops processes using Code Quality Inspection tools such as SonarQube and Synk.
- Experience in creating Unit, End to End, Functional and Regression Testing Frameworks.
Other
- Master’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field.
- Problem solver with can-do attitude, not afraid of facing new problems, technical challenges, delivery pressures
- Ability to clearly define problems, models and constraints from informal and flexible business requirements
- Tech leadership with teamwork spirit, quick adaptation to new environment
- Form collaborative working environment.