Machine Learning Scientist

Position: Machine Learning Scientist

Reports To: Chief of Data Science and AI

Location: Chicago, IL

Job Overview

As a machine learning scientist in our clients innovative and fast-paced team, you will be building machine learning models as well as designing and developing next generation AI applications that allow legal investigators and litigation professionals to filter millions of documents down to those most important to their case.

From your seat in our beautiful new office in downtown Chicago, you will have access to many teammates to help respond to clients timely. Our office is in the heart of the loop with very convenient access to all major public transportation lines. Please be aware that we are onsite with a traditional five-day workweek schedule. This is a fully in-person role.

Responsibilities & Duties

• Design and implement advancements in AI and GenAI-based modules.
• Design and implement new AI and GenAI functionality.
• Work with internal stakeholders on creating solutions tailored to the customer’s needs.
• Work on scalability and performance of AI functionality.

Characteristics

• Creativity and quick problem-solving abilities demonstrated in industry or academic projects.
• Strong collaboration and team playing skills.
• Oand time management skills to handle multiple competing demands.

Education & Experience

• M.S. or Ph.D. in Computer Science, BS in Computer Science.
• 3-4 years of industry work experience.
• Solid understanding of core ML concepts, algorithms, and evaluation metrics.
• Understanding of Large Language Models fundamentals.
• Hands-on experience with prompt engineering for specific tasks and domains. Skills in techniques like chain-of-thought prompting and in techniques to improve LLM performance and reduce hallucinations.
• Experience with Retrieval-Augmented Generation (RAG).
• Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
• Experience with cloud services (AWS, Azure, GCP) for data storage, model training, and deployment.
• Proficiency with Git and platforms like GitHub for code management.
• Experience with Docker.
• Understanding and implementation of continuous integration and continuous delivery practices.
• Understanding of data structures, algorithms, object-oriented programming (OOP), and system design.