Company Description
About Grab and Our Workplace
Grab is Southeast Asia's leading Super-App. 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 our Team
GrabFin is an aggregate of FinTech businesses spread across 6 countries in South East Asia, in the Payments, Lending and Insurance domains. We station our engineering teams in Bangalore, Singapore, Indonesia and Vietnam. We are excited to provide financial services to all participants of the Grab Ecosystem be it our Consumers, Drivers or Merchants. We build our products on fundamental market insights combined with advanced Data Science, Generative AI and engineering to bring the best product market fit across the cross section of our user base. This understanding of our ecosystem combined with world class engineering execution continues to create tremendous value for our customers.
GrabFin stations its data science team across Bangalore and Singapore. We aim to hire a Data Scientist to join our Bangalore office to expand the existing Bangalore team. The data scientist will work in a relatively flat team structure with an independent goal of building and manage critical data science models daily. You can expect to solve hard technical problems and grow into an expert on batch, real-time, and LLM-driven Data Science use cases. You will need experience with technology and data science.
You will be an Individual contributor reporting to a Senior Manager, Data Science and will work onsite at our office in Bangalore.
Job Description
Get to know the role
As Part Of This Role, You Will
- Develop an understanding of Payments architecture and its nuances across use cases and countries.
- Help build predictive models for payment method recommendations, downtime management, intelligent transaction retry, payments processor selection, and other such solutions, aiming to improve payments transactions and reduce failure rates.
- Use LLMs to power the next generation of payment experiences.
- Manage the end-to-end lifecycle of predictive models and AI agents, from development to deployment and optimization.
- Work with engineering, compliance & operation teams to create solutions and product changes informed by your findings and business inputs.
- Stay current with the latest AI/LLM research and new frameworks and incorporate them into practical applications.
The daily activities
- Predictive Modelling: Build predictive models using machine learning to solve for classification, ranking and online learning. Engineer features from internal data assets to build refined transaction and customer profiles.
- Generative AI Development: Design and deploy Generative AI solutions using prompt engineering, agent orchestration, and model fine-tuning (e.g., LoRA, PEFT). Build evaluation datasets and define guardrails for ongoing evaluation and monitoring.
- MLOps & Automation: Build end-to-end MLOps pipelines to automate model training, deployment, and monitoring. Track production performance and implement feedback loops for continuous improvement.
- Ownership and Collaboration: Design AI solutions by working backwards from our needs. Lead the delivery of AI capabilities, from concept through production deployment.
Qualifications
Essential Requirements
- 2+ years of relevant experience
- Core ML: Expert proficiency in Python, Spark, and SQL (Presto/Hive) with a command of fundamental ML concepts (Bagging, Boosting, Online Learning, Recommendation Engines).
- Generative AI & Agent Frameworks: Hands-on experience with Agentic frameworks (specifically LangGraph, LangSmith, or LangChain) and LLM orchestration.
- MLOps & Productionisation: Expertise in productionizing ML solutions with MLOps tools (MLflow, Kubeflow, TFX, SageMaker) and deploying scalable components on cloud platforms.
- Real-Time Streaming: Experience in the real-time implementation of machine learning solutions using Flink SQL and Flink SDK is a good to have
- Engineering Excellence: Adherence to clean coding, modular design, and version control (Git/GitHub).
- Balance model performance with business trade-offs (latency, cost, scalability).
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.
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.
