Machine Learning Engineer - APAC

Reposted 8 Days Ago
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Hiring Remotely in Malaysia
Remote
Senior level
Information Technology • Legal Tech • Analytics
The Role
Design, develop, evaluate, and productionize ML models and agentic solutions on Databricks and Microsoft Fabric. Build scalable ETL pipelines, perform feature engineering, run disciplined experiments, monitor models in production, and communicate statistical insights to stakeholders while supporting platform engineering and automation.
Summary Generated by Built In

Machine Learning Engineer

Do you have exceptional data capabilities?

Would you like to join a Global leader in Legal Analytics and Technology?

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.

Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here.

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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EEO Know Your Rights.

Skills Required

  • Bachelor's degree in Data Science, Statistics, Computer Science, or related field
  • Master's degree
  • Five or more years of experience in data and machine learning or closely related roles
  • Demonstrated expertise with Databricks, Microsoft Fabric, and Power BI (platform engineering, operating, maintenance, break/fix)
  • Ability to communicate technical and statistical concepts clearly to technical and non-technical stakeholders
  • Ability to work effectively with cross-functional and regional teams
  • Able to hold technical interviews across SQL, Python, data modelling & evaluations, statistical foundations, and ML algorithms
  • Experience with NLP (text preprocessing, topic modeling, classification, sentiment analysis)
  • Experience with Agentic models and Generative AI
  • Experience with workflow automation, ETL pipelines, and data pipeline orchestration
  • Experience with PowerApps and MLflow
  • Familiarity with version control and CI/CD for ML
  • Experience implementing model monitoring and A/B rollouts

RELX Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about RELX and has not been reviewed or approved by RELX.

  • Retirement Support Retirement support is positioned as a meaningful part of total rewards through a 401(k) plan with matching contributions, alongside other financial protections such as life and disability coverage. Tuition reimbursement and share purchase access further broaden the financial value of the package beyond base salary.
  • Leave & Time Off Breadth Leave and time off breadth appears strong, with generous vacation allowances, mental health days, and options like sabbaticals and tiered PTO by tenure. Parental and caregiving leaves are described in detail, reinforcing time-away benefits as a standout component of the overall package.
  • Wellbeing & Lifestyle Benefits Wellbeing and lifestyle benefits are supported by offerings such as mental health support (e.g., app access), EAP resources, gym-related perks, and wellness incentives. Flexible working hours and related work-life supports add to the perceived day-to-day value of benefits.

RELX Insights

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The Company
HQ: London
10,001 Employees
Year Founded: 1880

What We Do

RELX is a global provider of information-based analytics for professional and business customers across industries. We help scientists make new discoveries, doctors and nurses improve the lives of patients and lawyers win cases. We prevent online fraud and money laundering, and help insurance companies evaluate and predict risk. Our events enable customers to learn about markets, source products and complete transactions. In short, we enable our customers to make better decisions, get better results and be more productive. We do this by leveraging a deep understanding of our customers to create innovative solutions which combine content and data with analytics and technology in global platforms. RELX serves customers in more than 180 countries and has offices in about 40 countries. It employs approximately 30,000 people of whom almost half are in North America. We operate in four major market segments: Scientific, Technical & Medical; Risk & Business Analytics; Legal; and Exhibitions.

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