Level

RELX

Machine Learning Engineer - APAC

AI in this role

mlflowdatabricks
ai-evaluationnlp

Machine Learning Engineer


About our Company  

LexisNexis Legal & Professional, a division of RELX, is a global leader in providing information-based analytics and decision tools for professional and business customers. With a presence in over 150 countries and a workforce of 11,300 employees worldwide, we are committed to delivering exceptional service and innovative solutions.


About the Team

Our team, based in the APAC region, plays a crucial role in supporting all regional functions through comprehensive reporting and data-driven insights. We are currently undergoing an exciting transition, where we are enhancing our data capabilities and embracing Agentic Development, Machine Learning, and Predictive Analytics to better support our business objectives and drive growth. 

Our team is composed of high-performing professionals who collaborate across business units to deliver insights that shape strategic decisions. You’ll work closely with stakeholders across departments and geographies, including mentoring junior analysts and supporting organisational development initiatives. 


About the role

This role directly supports our strategic shift toward machine learning, predictive analytics, and Agentic development in the region, enabling faster and more reliable delivery of insights and outcomes for APAC stakeholders on our modern data platforms.


Responsibilities

  • Data Processing at Scale.  Clean, transform, and join raw datasets, handling missing data, outliers, normalization, and leakage prevention using SQL and Python.
  • Design and develop ML models tailored to business needs, leveraging statistical methods to ensure accuracy and reliability.  Apply classical and modern techniques including regression, classification, time series analysis, and hypothesis testing to build trustworthy models.
  • Implement ML algorithms with an emphasis on performance and interpretability.
    Select appropriate algorithms and use statistical techniques to optimize hyperparameters, reduce variance and bias, and manage class imbalance.
  • Conduct disciplined experiments to test and validate models.  Design experimental frameworks, use train validation test splits and cross validation, and interpret results with appropriate statistical significance and confidence intervals.
  • Feature engineering rooted in business and statistical understanding.  Create informative features through aggregation, encoding, interaction terms, and time windows; assess feature importance and stability over time.
  • Model evaluation using statistically sound metrics.  Evaluate with precision, recall, F1 score, ROC AUC, calibration, confusion matrices, and cost sensitive metrics appropriate to the problem.
  • Collaborate with data scientists to embed statistical insights into model design and validation, ensuring robust predictive analytics and practical deployment pathways.
  • Optimize and productionize models for reliability and speed.  Tune hyperparameters, apply regularization and ensembling, implement monitoring for drift and performance, and manage A/B rollouts on Databricks and related tooling.
  • Reporting and documentation that clearly communicates methodology, assumptions, statistical analyses, and business implications to technical and non-technical stakeholders.
  • Agentic creation for intelligent solutions that designs and implements autonomous, adaptive workflows using Agentic development principles to enable self-directed decision-making and dynamic integration across business processes.
  • Workflow Automation and Optimization which develops and refines automated pipelines for data processing, model deployment, and monitoring, leveraging tools such as Databricks and Microsoft Fabric to ensure scalability, efficiency, and minimal manual intervention.

Requirements

  • Master’s degree preferred, with a minimum of a Bachelor’s degree in Data Science, Statistics, Computer Science, or a related field.
  • Five or more years of experience in data and machine learning or closely related roles, demonstrating independent execution of best practices and end to end delivery from development and testing through production.
  • Demonstrates expertise in our technology stack (Databricks, Microsoft Fabric, and Power BI) to support platform engineering activities, including operating, maintaining, and providing break/fix coverage for core data platforms.
  • Excellent communication skills with the ability to translate technical and statistical concepts into clear, actionable insights for both technical and non-technical stakeholders.
  • Ability to work effectively with cross-functional teams across regions, fostering collaboration and knowledge sharing.
  • Support and encourage a high-performing team culture where treating everyone with respect is a core expectation, fostering inclusivity, trust, and accountability in all interactions.
  • Must be able to hold technical conversations across SQL, Python, Data Modelling & Evaluations, Statistical Foundations, and ML Algorithms during technical interview.
  • Experience in the following areas will be highly advantageous:
    • NLP (text preprocessing, topic modeling, classification, sentiment analysis)
    • Agentic models & Generative AI
    • Databricks
    • Microsoft Fabric (model administration & maintenance)
    • Workflow automation
    • ETL pipelines
    • PowerApps
    • MLflow
    • Data pipeline orchestration
    • Version control
    • CI/CD
    • Model monitoring
    • Power BI

Work in a way that works for you 
 

We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals. 

 
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: 
 

  • Flexible working arrangements 
  • Benefits for you and your family 
  • Access to learning and development resources 

 
Your recruiter will advise you on the full benefits package for your location 
 

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. 









We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.

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 or please contact 1-855-833-5120.

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Please read our Candidate Privacy Policy.

We are 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.

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How we rate this

Machine Learning Engineer - APAC at RELX rates 83 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

AI EvaluationNLPMlflowDatabricks

Questions you could be asked

  1. How do you decide that one model's output is better than another's for a given task?
  2. What NLP problem have you worked on, and how did you measure whether it actually worked?
  3. What are the limits of Mlflow that you've run into, and how did you work around them?
  4. What's a project where you used Databricks hands-on?
  5. How would you decide a model or AI system is ready to ship?

Adapt your resume

  • List these exact terms on your resume: AI Evaluation, NLP, Mlflow, and Databricks. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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