Senior Machine Learning Engineer

Company Description

About Grab and Our Workplace

Grab is Southeast Asia's leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we've got your back with everything. In Grab, purpose gives us joy and habits build excellence, while harnessing the power of Technology and AI to deliver the mission of driving Southeast Asia forward by economically empowering everyone, with heart, hunger, honour, and humility.

Job Description

Get to Know the Team

In the GrabMart Data Science team, you are at the heart of Grab's retail and grocery engine. We build and deploy AI/ML models that power seamless shopping experiences across our ecosystem. Our mission is to transform how millions shop. We achieve this by solving complex challenges in inventory intelligence, demand forecasting, and hyper-personalized discovery. Our goal is to ensure every user finds exactly what they need, right when they need it.

You will report to our Senior Data Science Manager and based onsite in our office in Petaling Jaya, Selangor.

Get to Know the Role

We are looking for Senior Machine Learning Engineers to lead high impact technical workstreams within our shopping ecosystem. You will manage technical projects from brainstorming to production—developing scalable DS architectures, deploying services, and ensuring model robustness. You will work as a technical expert, collaborating with Engineering, Product, and Analytics to provide advanced, data-driven solutions.

The Critical Tasks You Will Perform

• Extract Insights: You will analyze massive datasets (transactional, behavioral, and geospatial) to decode shopping patterns and improve the end-to-end journey for grocery and retail services.
• Develop AI Solutions:
  • Next-Gen User Experience: You will move beyond static interfaces to build agentic, conversational, and anticipatory experiences. You will predict shopping intent and brand preferences to power autonomous shopping assistants that can handle complex queries, automate re-ordering, and provide hyper-personalized discovery.
  • Service Reliability: You will build predictive models to safeguard the order lifecycle by identifying high-risk orders prone to cancellation, predicting fulfillment failures due to insufficient inventory, and flagging transactions requiring proactive intervention.
  • Demand Forecasting: You will create high precision, hyper-local spatio-temporal models using complex signals (weather, events, marketing). You will provide granular SKU-level predictions to improve supply chain readiness and minimize waste.
  • Demand Shaping: You will implement intelligent optimization algorithms to balance demand and supply in real-time. You will improve platform visibility and use contextual nudges spatially and temporally to balance demand with merchant/driver supply
  • Demand Generation: You will decode unique user shopping patterns to unlock new demand. You will build AI models for automated targeting and user segmentation to drive sustainable growth.
• Build, Deploy and Iterate: You will develop production-grade AI models. You will oversee the A/B testing lifecycle and implement real-time production monitoring to ensure long-term model health. You will adopt ML Operational Excellence practices to ensure vigorous versioning, automated testing, seamless deployment, performance monitoring, and continuous improvement of ML pipelines.
• Innovate: You will stay at the forefront of AI/ML research, contributing to the team's internal knowledge base and IP creation.
• Collaborate cross functionally: You will partner with Project Managers, Engineers, and Operations to integrate and scale solutions across the region.

Qualifications

What Essential Skills You Will Need

• Education: Master's degree in Machine Learning, Statistics, Computer Science, Economics, Operations Research, or a related quantitative field.
• Experience: 5+ years of experience as a Data Scientist, with a proven track record in E-commerce, Quick-Commerce, or Marketplace domains.
• Technical Depth: Deep understanding of ML/DL, data mining, and optimization algorithms. Proficiency in frameworks like TensorFlow or PyTorch.
• Programming: Proficient in Python or Scala.
• Soft Skills: Motivated, independent learner, communicate and articulate well on complex insights to non-technical stakeholders
• Versatile: Work well in a startup environment and manage multiple high-priority workstreams.
• Engineering Excellence: Experience with CI/CD principles for ML (MLOps).

Good-to-have (Preferred):

• Specialized Experience: Build large-scale recommender systems, customer segmentation, or supply-chain optimization.
• Big Data: Hands-on experience with Spark, Flink, or Kafka for large-scale/real-time data processing
• Generative AI:
  • Experience in fine-tuning LLMs and building LLM-based applications for commerce (e.g., shopping assistants, automated cataloging).
  • Familiarity with agentic development tools (e.g., LangChain, AutoGPT, CrewAI) and experience building autonomous agentic systems to solve complex, multi-step commerce workflows.

Additional Information

Life at Grab

We care about your well-being at Grab, here are some of the global benefits we offer:

• We have your back with Term Life Insurance and comprehensive Medical Insurance.
• With GrabFlex, create a benefits package that suits your needs and aspirations.
• Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
• We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.
• Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours

What We Stand For At Grab

We are committed to building an inclusive and equitable workplace that provides equal opportunity for Grabbers to grow and perform at their best. We consider all candidates fairly and equally regardless of nationality, ethnicity, race, religion, age, gender, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.