Machine Learning Engineer  at Harbor

Chicago, Illinois, United States -

Full Time

Start Date

Immediate

Expiry Date

19 Dec, 25

Salary

127754.0

Posted On

20 Sep, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Science, Operations Research, Python, TensorFlow, PyTorch, Apache Airflow, Azure Cloud Services, Data Pipelines, Real-Time Systems, AI Frameworks, Automation Roadmaps, Code Reviews, Knowledge Sharing, Large Language Models, DAGs

Industry

Business Consulting and Services

Description

EMPLOYER: Harbor Employees LLC POSITION: Machine Learning Engineer WORKSITE: 200 North LaSalle, Suite 2020, Chicago, IL 60601 (Part-time telecommuting is permissible (up to 4 days per week) from within the Chicago, IL metropolitan area) OFFERED WAGE: $127,754.00 / Year JOB DUTIES: Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. Continuously research and implement best practices in machine learning and cloud infrastructure to enhance system capabilities and performance. Assist with and participate in code and PR reviews, best practices in development, document processes, and team-wide knowledge-sharing initiatives. Work closely with the artificial intelligence (AI) team to support and fine-tune large language models (LLMs), ensuring optimal performance and efficiency. Design, implement, and maintain data pipelines and Azure cloud infrastructure for deploying real-time machine learning models. Develop custom Apache Airflow solutions and design optimized DAGs to ensure seamless integration, automation, and efficiency of data processes. Part-time telecommuting is permissible (up to 4 days per week) from within the Chicago, IL metropolitan area. Minimum Education and Experience Requirements: Master’s degree, or foreign equivalent, in Machine Learning, Data Science, Operations Research, or related field plus three (3) years of experience as a data engineer developing machine learning workflow systems. SPECIAL REQUIREMENTS: Must include at least three (3) years of experience including with: Python; machine learning frameworks including TensorFlow and PyTorch; Apache Airflow; Azure cloud services; developing real-time intelligent workflow systems for professional services. Must include at least one (1) year of experience: designing and managing scalable, real-time data pipelines, optimizing machine learning models for high-performance, industry-specific applications, and building adaptive AI frameworks within these sectors; developing automation roadmaps and advising on AI solutions to meet business objectives in compliance critical environments. About Us: Harbor is the preeminent provider of expert services across strategy, legal technology, operations, and intelligence. Our globally integrated team of 800+ strategists, technologists, and specialists navigate alongside our clients – leading law firms, corporations, and their law departments – to provide essential resources and invaluable insights. Anchored in a rich heritage of deep knowledge, steadfast relationships, and mutual respect, our unwavering dedication lies in shaping the future of the legal industry and fostering enduring partnerships within our community and ecosystem. Harbor is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, sexual orientation, gender identity, marital status, civil union status, national origin, ancestry, age, parental status, disabled status, veteran status, or any other legally protected classification, in accordance with applicable law.

Responsibilities

The Machine Learning Engineer will collaborate with cross-functional teams to translate business requirements into technical solutions and enhance system capabilities through research and implementation of best practices. They will also work closely with the AI team to support and fine-tune large language models while maintaining data pipelines and Azure cloud infrastructure.