Machine Learning Engineer

Job Title:

Machine Learning Engineer (GenAI / LLM)

Skills:

Artificial Intelligence, Machine Learning Operations (ML Ops), Machine Learning (ML), LangChain, Python, Large Language Models (LLMs), Data Science, and Agentic frameworks

About Us:

iceDQ.ai is a product-based company in Stamford, CT. Our data reliability platform is utilized by the top Fortune 500 companies in banking, insurance and healthcare. If you are interested in building AI agents that are integrated into the product and used by some of the leading companies, please read ahead.

Job Overview:

For our product development, we are seeking an innovative Machine Learning Engineer with a robust background in generative AI, prompt engineering, and AI agents. The ideal candidate will have hands-on experience with retrieval-augmented generation (RAG) and cutting-edge frameworks like LangChain and Lang Graph, coupled with advanced Python programming skills.

This role involves developing state-of-the-art AI Agents that drive intelligent, interactive systems and contribute to a transformative AI strategy.

Work closely with data engineers, software engineers, and product managers to develop AI agents for our product.

Job Responsibilities:

AI Agents Development: Build and refine AI agents capable of performing autonomous tasks and engaging in complex interactions. Enhance AI agent behavior using reinforcement learning, multi-agent systems, and prompt-based techniques.

Prompt Engineering: Create and optimize prompt engineering strategies to refine the outputs of AI models. Continuously iterate on prompt designs to maximize efficiency and contextual accuracy.

Retrieval-Augmented Generation (RAG): Integrate RAG techniques to enhance generative models with dynamic data retrieval, boosting response relevance. Develop pipelines that seamlessly combine generative outputs with real-time information retrieval.

Framework Integration: Leverage LangChain, LangGraph, and similar frameworks to construct scalable, modular AI systems. Collaborate with cross-functional teams to integrate these frameworks into broader machine learning and production pipelines.

Experience:

• Proven track record as a Machine Learning Engineer, Data Scientist, or similar role with a focus on generative AI and AI agents.
• Expertise in generative AI techniques and prompt engineering.
• Demonstrable experience with prompt engineering and retrieval-augmented generation (RAG) methodologies.
• Experience developing and managing AI agents, including knowledge of reinforcement learning or multi-agent systems.
• Proficiency in Python with extensive experience in machine learning libraries and frameworks.
• Familiarity with LangChain, LangGraph, or similar frameworks.
• Experience deploying machine learning models and AI agents in production environments.
• Familiarity with cloud computing platforms (AWS, GCP, Azure) and containerization tools.
• Background in natural language processing (NLP) and large language model development.

Education:

Bachelor’s or master’s degree in computer science, Data Science, Electrical Engineering, or a related field.