Job Requirements
Key Responsibilities
AI & Machine Learning Development
- Design, build, and deploy AI/ML models for classification, prediction, NLP, computer vision, and generative AI use cases.
- Fine-tune, optimize, and implement Large Language Models (LLMs) such as GPT, Llama, Falcon, or domain-specific models.
- Develop AI agents, Retrieval-Augmented Generation (RAG) systems, and automation workflows.
Data Engineering & ETL Development
- Design, build, and optimize scalable ETL workflows using Informatica, SnapLogic, and AWS Glue.
- Develop and maintain robust data pipelines for ingestion, transformation, and loading into data warehouses.
- Manage and monitor data warehouse clusters and AWS EMR to ensure high availability, performance, and security.
- Write and optimize complex SQL queries for data extraction, transformation, and reporting.
- Implement data quality checks, validation frameworks, and data governance best practices.
Collaboration & Operations
- Work closely with data architects, analysts, and business stakeholders to understand requirements and deliver scalable solutions.
- Automate workflows and operational processes using Python for improved efficiency.
- Troubleshoot and resolve data-related issues in production environments.
- Ensure compliance with organizational data security standards and industry best practices
Work Experience
Required Skills & Expertise
AI/ML & Advanced Analytics
- Experience with cloud AI services on Azure, AWS, or GCP.
- Familiarity with MLOps tools such as MLflow, Kubeflow, Docker, CI/CD pipelines.
- Understanding of RAG systems, embeddings, prompt engineering, and LLM evaluation.
- Exposure to GPU computing, distributed training, or ONNX optimization.
- Experience with computer vision, reinforcement learning, or multimodal AI models.
Data Engineering & Cloud Technologies
- Strong SQL expertise (query optimization, stored procedures, performance tuning).
- Hands-on experience with Informatica for ETL development.
- Proficiency with SnapLogic for integration and data flow automation.
- Experience with AWS Glue (serverless ETL) and AWS EMR for large-scale data processing.
- Experience with data warehouse platforms such as Snowflake, Redshift, BigQuery, or similar.
- Strong programming skills in Python for scripting, automation, and data processing.
- Understanding of data modeling, data governance, and data quality frameworks.
- Familiarity with cloud platforms (AWS, Azure, GCP) and modern data services.
Additional Skills
- Excellent problem-solving abilities and analytical thinking.
- Strong communication skills with the ability to work in a global, cross-functional environment.
Preferred Qualifications
- Bachelor's degree in Computer Science, Information Technology, or equivalent discipline.
