Machine Learning Engineer, MLOps Engineer (Remote)

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create digital marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realise their financial goals and help them to save time and money.

We operate across a range of markets, from financial services to healthcare, automotive, agrifinance, insurance, and many more industry segments.

We invest in people and new advanced technologies to unlock the power of data and to innovate. A FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 23,300 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com.

We are looking for an experienced MLOps Engineer to build and scale machine learning solutions that address critical challenges in the healthcare revenue cycle. You will report to Experian Health and focus on operationalizing ML models, ensuring deployment pipelines, and maintaining scalable, secure, and ML infrastructure on AWS, collaborate with data scientists, software engineers, and product teams to bring ML products from prototype to production, with a emphasis on automation, monitoring, and continuous improvement.

• You'll have opportunity to:
  • Develop scalable MLOps pipelines for model training, validation, deployment, and monitoring using AWS services
  • Implement infrastructure as code and CI/CD workflows to support rapid experimentation and reliable production releases
  • Collaborate with data scientists to productionize ML models and ensure reproducibility, versioning, and traceability
  • Monitor model performance and data drift in production environments, and implement automated retraining and alerting mechanisms
  • Improve ML workflows using tools such as SageMaker, Airflow, Docker, Kubernetes (EKS), and Step Functions
  • Ensure compliance with healthcare data standards and security best practices (e.g., HIPAA)

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
• 3+ years' experience in MLOps, DevOps, or ML engineering roles
• 3+ years' experience with AWS services for ML (e.g., SageMaker, Lambda, Step Functions, S3, ECR, CloudWatch)
• Proficiency with containerization and orchestration tools (Docker, Kubernetes/EKS).
• 3+ years' experience with ML lifecycle tools such as MLflow, TensorFlow Serving, or Kubeflow and with CI/CD pipelines, infrastructure as code (e.g., Terraform, CloudFormation), and monitoring/logging tools
• Experience in the healthcare domain, especially with claims or EHR data, and familiarity with standards like ICD and CPT
• Exposure to NLP, Bayesian modeling, or real-time ML systems
• Familiarity with Agile development methodologies
• AWS certifications (e.g., Machine Learning Specialty, DevOps Engineer)

Benefits/Perks:

• Great compensation package and bonus plan
• Core benefits including medical, dental, vision, and matching 401K
• Flexible work environment, ability to work remote
• Flexible time off including volunteer time off, vacation, sick and 12-paid holidays
• Explore all our exciting benefits here: https://yourexperianbenefits.com/cand-index.html

At Experian, our people and culture set us apart. We're deeply committed to creating an environment where everyone feels they belong and can excel. From inclusion and authenticity to work/life balance, development, wellness, collaboration, and recognition, we focus on what truly matters. Our people-first approach has earned us global recognition: World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ 2025 in 26 countries, and Glassdoor Best Places to Work 2024, among others.

Want to see what life at Experian is really like? Explore Experian Life on social or visit our careers site.

Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay range for this position is listed above. Within this range, individual pay is determined by work location and additional factors such as job-related skills, experience, and education. You will be also eligible for a variable pay opportunity.

Experian is proud to be an Equal Opportunity Employer for all groups protected under applicable federal, state and local law, including protected veterans and individuals with disabilities. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.