WCR- Quantitative Research - Associate

Job Responsibilities:

• Design, develop, and deploy state-of-the-art AI/ML/LLM/GenAI solutions to meet business objectives.
• Develop and maintain automated pipelines for data, ensuring scalability, reliability, and efficiency.
• Implement optimization strategies to fine-tune generative models for domain specific use cases, ensuring high-quality outputs in summarization and text generation.
• Conduct thorough evaluations of generative models iterate on model architectures and implement improvements to enhance overall performance in AI/ML applications.
• Implement monitoring mechanisms to track AI/ML solutions performance in real-time and ensure model reliability.
• Communicate AI/ML/LLM/GenAI capabilities and results to both technical and non-technical audiences.
• Stay informed about the latest trends and advancements in the latest AI/ML/LLM/GenAI research, implement cutting-edge techniques, and leverage external APIs for enhanced functionality.

Required Qualifications:

• Master's with at least 2+ years experience in Computer Science, Data Science, Machine Learning, or a related field.

• Proficiency in Python for model development, experimentation, and integration with the LLM APIs.
• Ability to identify and address AI/ML/LLM/GenAI challenges, implement optimizations, and fine-tune models for optimal performance in AI/ML applications.
• Experience with cloud platforms (preferably AWS), containerization technologies (Docker and Kubernetes), and microservices design, implementation, and performance optimization.
• Proficient in building AI Agents (e.g., LangChain, LangGraph), integration of tools, and RAG-based solutions, Knowledge Graphs (e.g., neo4J).
• Experience developing end-to-end data workflows and ETL pipelines using Python and Databricks.
• Strong understanding of data modeling, normalization, and database design principles.
• Experience developing, debugging, and maintaining code in a large corporate environment using one or more modern programming languages and database querying languages.
• Ability to gather, analyze, and synthesize large, diverse data sets and to develop visualizations and reports in support of continuous improvement of applications and systems.
• Strong collaboration skills to work effectively with cross-functional teams, communicate complex concepts, and contribute to interdisciplinary projects.