ML Ops Engineer

** Please note that the selected individual for this role will be expected to work in our Raleigh, NC location from the time of joining. If you reside outside of the Raleigh region and you are unable or unwilling to relocate, then please consider other roles across our organization that might allow for remote locations. **

About our Team:
LexisNexis 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.

Nexis Solutions, a division of LexisNexis, is seeking a Data Scientist who will focus on search and be dedicated to the creation of next-generation search relevance techniques and strategies for LexisNexis, dramatically improving how our users search and find the answers to their research questions. This role should be able demonstrate versatility, collaborate across teams, and be enthusiastic in tackling new problems as we continue to push technology forward

About the Role:

LexisNexis is at the forefront of developing cutting-edge AI and machine learning solutions. We're looking for an experienced MLOps Engineer to join our dynamic team. The ideal candidate will be responsible for implementing, managing, and optimizing end-to-end machine learning workflows, from model deployment to monitoring and scaling in cloud environments. If you are passionate about building scalable and reliable systems and have expertise in modern DevOps and MLOps tools, we would love to hear from you.

As a machine learning operations engineer on our team, you will develop and implement a strategy for continuous improvement of our Machine Learning Ops including versioning, testing, automation, reproducibility, deployment, monitoring, and data privacy.

Responsibilities:

• Design, implement, and manage end-to-end machine learning pipelines in a cloud environment (primarily AWS).
• Automate model deployment workflows using CI/CD tools like Jenkins, with experience in Blue/Green deployment strategies.
• Leverage AWS services (EC2, ASG, ELB, etc.) to deploy, scale, and secure machine learning models and applications.
• Work with infrastructure-as-code (CFTs in JSON/YAML) for provisioning and maintaining cloud resources.
• Manage containerized applications using Docker and Kubernetes to ensure smooth deployment, scaling, and monitoring.
• Implement and maintain secure IAM roles, policies, and other security best practices across cloud systems.
• Optimize model serving frameworks such as TorchServe for production use, ensuring performance and reliability.
• Maintain and monitor APIs using RESTful standards and tools like Swagger for model endpoints.
• Design and implement dashboards for monitoring model performance, health, and infrastructure using relevant tools.
• Collaborate with data scientists, data engineers, API engineers, and the dev ops team.
• Scale up production systems to handle increased demand from new products, features, and users.
• Continuously monitor and improve the performance, security, and scalability of deployed models and infrastructure.
• Provide visibility into the health of our data platform (comprehensive view of data flow, resources usage, data lineage, etc) and optimize cloud costs.
• Develop and report on ML Ops metrics such as deployment frequency, lead time for changes, mean time to restore, and change failure rate.
• Automate and handle the life-cycle of the systems and platforms that process our data.

Preferred Qualifications:

• BS in Software Engineering, Data Engineering, Computer Science or related field.
• 3+ years of relevant work experience.
• Please provide your LinkedIn and private GitHub URLs if available.

Technical Skills:

• Strong background in DevOps and build automation.
• Knowledge of current principles and frameworks for ML Ops.
• Experience with ML model serving frameworks such as Ray Serve, MLFlow Inference, KubeFlow, TorchServe, Triton, or SageMaker.
• Experience with serverless technologies such as AWS Lambda or Fargate.
• Python and/or Scala background.
• Experience with Apache Spark preferred.
• Knowledge of AWS, GCP, Azure, or other cloud platform.
• Experience with data lineage and experiment tracking software such as MLFlow, DVC, DataHub, or DataZone.
• Experience with CI/CD pipelines, including Jenkins or Git Actions.
• Experience with Docker containerization or Kubernetes orchestration.
• Experience in improving data security and privacy, and managing and reducing cloud costs.
• Knowledge of API development and machine learning deployment.
• Experience with SonarQube for code quality analysis and integration into the CI/CD pipeline.
• Excellent communication skills and the ability to work effectively in cross-functional teams.

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.

Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive

Working for you:

We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:

• Health Benefits: Comprehensive, multi-carrier program for medical, dental and vision benefits
• Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan
• Wellbeing: Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time-off Programs
• Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity
• Family Benefits, including bonding and family care leaves, adoption and surrogacy benefits
• Health Savings, Health Care, Dependent Care and Commuter Spending Accounts
• Up to two days of paid leave each to participate in Employee Resource Groups and to volunteer with your charity of choice

About the Business:

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. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis and Nexis services.

LexisNexis, a division of RELX, is an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form: https://forms.office.com/r/eVgFxjLmAK , or please contact 1-855-833-5120.

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