Machine Learning Engineer III

## .Machine Learning Engineer III page is loaded## Machine Learning Engineer III locations:
Raleigh, NCtime type:
Full time posted on:
Posted Todayjob requisition :
R107735
** About the Business:
** Lexis Nexis Legal & Professional provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis and Nexis services.
** About the Team:
** Lexis Nexis Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX (), a global provider of information-based analytics and decision tools for professional and business customers. Our company has been a long-time leader in deploying AI and advanced technologies to the legal market to improve productivity and transform the overall business and practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model from today’s top model creators for each individual legal use case.

The company employs over 2,000 technologists, data scientists, and experts to develop, test, and validate solutions in line with RELX Responsible AI Principles ().
*
* About the role:

** This position performs
** software development and applied machine learning
** assignments within a defined functional area or product line. The role
** contributes to the design, implementation, training, evaluation, and deployment of machine learning models and supporting data pipelines
** under the guidance of senior engineers. This position collaborates closely with cross-functional teams, including software engineers, data engineers, and product partners, to translate well-defined business or research requirements into machine learning solutions. The role
** focuses on building, testing, and improving ML components within existing systems while continuing to develop technical depth and best practices.
**** Conditions of Employment - Ability to work a Hybrid schedule reporting to Raleigh, NC Office location             **⸻
** Requirements:*
* • 1 - 3+ years experience in Machine Learning Engineering, Data Science, or Software Engineering with a
** strong ML focus*
* • BS in Computer Science, Engineering, Mathematics, Statistics, or a related field, or equivalent practical experience⸻TECHNICAL

SKILLS:

• Working knowledge of machine learning fundamentals, including supervised and unsupervised learning techniques
• Proficiency in at least one programming language commonly used in ML development (e.g., Python, Java, or Scala)
• Experience with common ML libraries and frameworks (e.g., PyTorch, Tensor Flow, scikit-learn)
• Familiarity with data manipulation, feature engineering, and data validation techniques
• Basic understanding of data modeling concepts and data storage systems (e.g., relational databases, data lakes)
• Experience working with SQL and/or other data query languages
• Familiarity with software development methodologies such as Agile
• Understanding of ML model evaluation, experimentation, and performance metrics
• Exposure to ML lifecycle practices including model training, testing, versioning, and deployment
• Ability to read, understand, and contribute to technical design documents
• Ability to debug and resolve moderately complex issues in ML pipelines or model behavior
• Good oral and written communication skills
• Willingness to learn new tools, technologies, and ML best practices⸻
** Responsibilities:*
* • Collaborate with software engineers, data engineers, and product stakeholders to understand requirements and contribute to ML solutions
• Implement machine learning models, data preprocessing pipelines, and evaluation workflows under established designs
• Write and maintain clean, well-tested, and well-documented code following team standards
• Assist in debugging, tuning, and improving model performance and data quality issues
• Participate in code reviews and apply feedback to improve code quality and ML practices
•…