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 Our team develops production-grade robotics and autonomy capabilities for the urban environments of Southeast Asia. We are advancing perception, planning, and control step by step, with safety evidence as the gate for every milestone. We focus on building robust system capabilities, scaling with uncompromised quality, and collaborating with industry leaders while investing in in-house expertise where it differentiates us. We are a senior, hands-on engineering group that prizes operational excellence, clear interfaces, and reproducible pipelines. Get to know the Role As a Lead MLOps Engineer, you'll be a core member of our foundational infrastructure team. Your mission is to lead the development of critical pipelines and workflows that enable the entire team to train, validate, and deploy models. You'll have hands-on ownership of essential components of our MLOps and simulation platform, directly impacting the team's development velocity and the reliability of our systems. You'll be based at Grab One North Singapore office and report to a Head of Engineering, contributiing directly to both technical and strategic leadership. The Critical Tasks You Will Perform Own and operate the data pipelines responsible for ingesting, processing, and curating robotics datasets. Lead the design and implementation of our core MLOps workflows, including CI/CD for model training, data versioning, and large-scale validation.. Partner with modeling engineers to understand their requirements and build the tools and services that accelerate their research and development. You participate in code and design reviews to maintain our high development standards. You engage in service capacity and demand planning, performance analysis, tuning, and optimization. Collaborate with engineers, data scientist teams to translate business needs into data solutions, implementing and deploying these solutions at scale. Mentor other engineers through code reviews, design discussions, and knowledge sharing. What Essential Skills You Will Need You have: At least 5 years of extensive experience in Robotics, Autonomous systems, Machine Learning, Statistics, Applied Mathematics, Computer Science, Economics, Operations Research, or a related fields. Experience with machine learning, deep learning, data mining, algorithmic foundations of optimization. Knowledge of model compression, quantization, and techniques for optimizing inference latency and cost. Familiarity with GPU/TPU acceleration and distributed inference architectures Proficiency in Python as well as deep learning frameworks (TensorFlow, PyTorch) and deployment tools (ONNX, tf-serving, TorchServe, Triton Inference Server) Hands-on experience building and managing CI/CD pipelines for machine learning (e.g., GitLab CI, Kubeflow, MLflow) Experience with model versioning, CI/CD for ML, containerization (e.g., Docker), and cloud-based deployment (AWS, GCP, Azure) 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. #J-18808-Ljbffr