Data Engineer

Your contribution to the team:
A collaborative spirit and excellent communication skills.
The ability to handle end to end SDLC phases from requirement gathering to implementation.
A knack for translating complex requirements into actionable development tasks.
A passion for design and hands-on coding experience
A proactive approach to testing, troubleshooting, and refining our applications.
The ability to work with cross-functional teams and do software integration.

Required Skill and Experience

Experience in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
Experience in Design, develop, and fine-tune machine learning models, particularly those involving LLMs and generative AI.
Experience with AWS services, especially Bedrock, S3, EC2, and Lambda Familiarity with ML Ops practices and tools for model deployment and monitoring.
Experience with AWS SageMaker for model development and model deployment.
Experience with developing and deploying AI Agents for business problems.
Experience in optimizing and adapt prompt engineering strategies to improve model performance and relevance.
Experience with LLMs (e.g., OpenAI, Anthropic, Cohere) and prompt engineering.
Experience in understanding quantitative/
statistical/ML/AI modeling methodologies.
Experience in ML engineering, including hands-on experience with Generative AI/LLMs.

Preferred Skill and Experience

Experience in building and maintaining scalable data pipelines and APIs to support ML workflows.
Knowledge of data privacy and security best practices in cloud environments.
Familiarity with containerization (Docker) and container orchestration is a plus.