Senior Machine Learning Engineer (Business Observability and Insights)

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.

Get to know the Role

The Senior Machine Learning Engineer will report into the Senior Engineering Manager and work onsite at Grab One North Singapore office. You'll focus on designing and deploying large-scale anomaly detection and root cause analysis systems critical to our core Fulfilment Services. You'll build a robust system that not only identifies business anomalies but also provides explainable interpretations. The system's output will include identifying the causes of these anomalies and offering actionable recommendations for their resolution or mitigation.

The Critical Tasks You Will Perform

• Design and deploy a large-scale, real-time Anomaly Detection and Root Cause Analysis (RCA) platform critical to core Fulfilment Services.
• Develop and architect the core components of the RCA system to provide explainable interpretations of anomalies, including identifying underlying causes and generating actionable recommendations for resolution or mitigation.
• Define and drive the technical roadmap for the evolution of the anomaly detection and root cause analysis platform in collaboration with the Tech Lead.
• Explore and implement state-of-the-art ML techniques to detect a variety of anomalies across different kinds of business and application performance metrics.
• Collaborate with Product Managers and Product Analysts to design intelligent anomaly detection systems that are robust in dynamic environments (e.g. holidays, events, natural disasters).
• Own the full software development lifecycle of the platform, including identifying and resolving performance bottlenecks, conducting service capacity/demand planning, software performance analysis, and participating in code/design reviews.

What Essential Skills you will Need

• You have a Master Degree in Computer Science/ Machine Learning or related fields, with at least 2 years of industry experience building and scaling production ready complex machine learning services.
• You have experience developing and integrating advanced models such as forecasting, causal ML, or LLM reasoning models into a cohesive and high-throughput ML System.
• You have proficiency in Python, coupled with an understanding of software engineering best practices, architectural design patterns, and experience writing readable, maintainable, and testable code.
• You have experience with full software development lifecycle of complex machine learning services, including developing and productionizing ML Pipelines using modern technologies (e.g. Airflow, MLFlow, or similar orchestrators).
• You have experience with any ML framework, such as TensorFlow or PyTorch
• You have hands-on experience with big data processing frameworks, such as Spark.

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 enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer, we consider all candidates fairly and equally regardless of nationality, ethnicity, religion, age, gender identity, sexual orientation, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.