Senior Machine Learning Engineer II

Machine Learning Engineer

LexisNexis 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. This position performs highly complex machine learning research, design, and development assignments across multiple systems or product lines. The role provides technical leadership in the design, implementation, evaluation, and deployment of large-scale machine learning systems and supporting data pipelines.

Requirements:

• 6+ years of experience in Machine Learning Engineering, Data Science, or Software Engineering with significant applied ML responsibilities
• BS in Computer Science, Engineering, Mathematics, Statistics, or a related field required; MS or PhD or equivalent practical experience preferred

Technical Skills:

• Deep expertise in machine learning algorithms and techniques, including supervised, unsupervised, and advanced modeling approaches
• Expert proficiency in one or more ML development languages (e.g., Python, Java, Scala)
• Extensive hands-on experience with machine learning frameworks and libraries (e.g., PyTorch, TensorFlow, scikit-learn)
• Proven experience designing and owning end-to-end, production-scale ML systems, including data ingestion, feature platforms, training, evaluation, deployment, and monitoring
• Strong understanding of data modeling principles and experience working with large-scale structured and unstructured data
• Strong proficiency with SQL and experience working with distributed data storage and processing systems
• Experience deploying, monitoring, and maintaining ML models in complex production environments
• Strong knowledge of software engineering best practices, including system design, testing strategies, CI/CD, and code quality standards
• Advanced knowledge of Agile and other development methodologies
• Strong research skills with the ability to evaluate, adapt, and operationalize new ML techniques
• Ability to diagnose and resolve highly complex issues related to model performance, data quality, system scalability, and reliability
• Strong ability to influence technical direction and align ML solutions with business goals
• Excellent oral and written communication skills

Responsibilities:

• Lead the design and implementation of complex, production-grade machine learning systems across multiple components or services
• Own the technical direction and execution of major ML initiatives or features
• Collaborate with product, engineering, and data stakeholders to shape ML strategy and translate ambiguous problems into scalable solutions
• Provide architectural guidance and review ML system designs and implementations
• Establish and promote best practices for ML development, testing, deployment, and monitoring
• Debug, optimize, and resolve the most complex ML and system-level issues
• Mentor and technically guide junior and mid-level machine learning engineers
• Contribute to project planning, estimation, and delivery for ML initiatives
• Evaluate and introduce new tools, frameworks, and methodologies to improve ML platform capabilities
• Ensure ML solutions meet performance, reliability, and quality standards in production
• Operate effectively across development environments and drive cross-team collaboration
• Keep abreast of industry trends and emerging technologies in machine learning and applied AI
• All other duties as assigned

Work in a way that works for you: We promote a healthy work/life balance across the organization. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals. U.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local market rates. This job is eligible for an annual incentive bonus.