Lead Machine Learning Platform Engineer

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 Team

You'll join a team building production-grade robotics and autonomy systems for urban environments across Southeast Asia. We advance perception, planning, and control capabilities step by step, using safety evidence as the gate for every milestone. We focus on building reliable systems, scaling without compromising quality, and collaborating with industry partners while developing in-house expertise where it sets us apart.

We are a senior, hands-on engineering group that values clear interfaces and reproducible pipelines.

Get to Know the Role

As a Lead MLOps Engineer, you'll report to the Head of Engineering and work from our One North Singapore office. You'll contribute to both technical leadership and strategic decisions for our foundational infrastructure team. Your mission is to develop the pipelines and workflows that help the team to train, validate, and deploy models. You'll have hands-on ownership of key components of our MLOps and simulation platform.

The Critical Tasks You Will Perform

• You'll design and implement data pipelines that ingest, transform, and curate robotics datasets (sensor data, logs, annotations) for model training and validation workflows.
• You'll build MLOps workflows that automate model training, track experiments, version datasets, and ensure reproducible training runs across the team.
• You'll develop deployment infrastructure that packages models for production, manages model artifacts, and orchestrates inference serving for real-time robotics applications.
• You'll create internal tools and APIs that modelling engineers use to submit training jobs, monitor progress, and access trained models.
• You'll improve inference pipelines for latency and throughput, implementing model compression and hardware acceleration (GPU/TPU) techniques for production robotics systems.
• You'll design monitoring and alerting systems that track model performance, data drift, and system health in production environments.
• You'll guide team members on MLOps architecture decisions, review technical designs, and establish standards for machine learning infrastructure.

What Essential Skills You Will Need

To perform the tasks above, you'll need:

• At least 5 years of experience building MLOps infrastructure, with at least 1 year leading architecture decisions. You have designed pipelines for data ingestion, model training, and deployment workflows.
• Experience with deep learning frameworks (PyTorch or TensorFlow) and experiment tracking tools to build infrastructure for distributed training and reproducible experiments.
• Experience building end-to-end MLOps workflows using tools such as Kubeflow, MLflow, or GitLab CI, including CI/CD for machine learning, data versioning (DVC or similar), and automated model testing.
• Experience deploying and optimising models for production using serving technologies (such as Triton or TorchServe) and optimization techniques (quantization, pruning) to achieve low-latency inference on GPU/TPU hardware.
• Experience managing machine learning infrastructure using Kubernetes, Docker, and infrastructure-as-code tools, with proficiency in Python for building data pipelines and MLOps tooling.

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.