Get to Know the Team

Welcome to Dev-AI at Grab! Our team focuses on empowering Grab engineers through AI innovation, combining in-house solutions and third-party technologies to elevate application development, testing, and automation efforts. By improving workflows, we aim to advance efficiency and productivity for all engineering teams across Grab.

Get to Know the Role

As part of your role, you'll be reporting to the Head of Engineering and collaborating with various teams to design AI tools that simplify and enhance the engineering process. You will identify opportunities for optimization within the Software Development Lifecycle, drive impactful AI initiatives, and ensure alignment with Grab's scalability and overall objectives.Your position will require technical leadership, and fostering innovation across Grab's engineering teams. You'll be based onsite at Grab Singapore's office, located at One-north.

The Critical Tasks You Will Perform

• You will develop and implement approaches targeted at improving datasets, including annotations and synthetic data creation, alongside fine-tuning methods like adapters and prompt tuning, and model optimization strategies such as quantization and pruning.
• You will apply the latest AI research to construct robust, scalable, and efficient ML systems that are ready for production.
• You will work hand-in-hand with engineering, research, and product teams to craft customised AI solutions that meet specific business requirements.
• You will design automated workflows to enhance the model training, evaluation, deployment, and monitoring processes, ensuring efficiency and scalability.
• You will offer mentorship and technical leadership to team members, fostering a culture centred around continuous improvement and innovation.

What Essential Skills You Will Need

• You have over 6 years of expertise in building and deploying AI/ML platforms, with hands-on involvement in providing technical leadership, mentoring engineers, or managing technical projects.
• You have knowledge of contemporary AI methods such as deep learning, transformers, generative models, and multimodal architectures is essential, along with proficiency in ML frameworks like PyTorch, TensorFlow, or Hugging Face.
• You also have knowledge of fine-tuning methodologies (e.g., PEFT, adapters, LoRA), dataset preparation techniques (e.g., annotation, augmentation, synthetic generation), and optimization strategies (e.g., quantization, pruning, distillation).Knowledge of optimization techniques such as quantization, pruning, and distillation.
• You can collaborate with product teams to implement AI solutions in live-production environments.
• You have experience translating cutting-edge AI research into workable, production-ready systems that align with project goals.
• You are proficient in Python and familiarity with tools like Spark, Ray, or Dask for large-scale data handling. Knowledge of engineering practices including CI/CD, containerization, microservices, and cloud infrastructure (AWS, GCP, Azure)
• You have history of success in leading technical initiatives, mentoring team members, and working with diverse teams (technical and non-technical) to drive AI-focused projects forward.