Shape AI that powers the future of financial access across Southeast Asia. You’ll play a key role in building and scaling systems that use AI to solve meaningful problems, from fraud detection and risk modeling to personalized experiences. This role combines senior-level engineering depth with team leadership, reporting directly to the Head of AI. You’ll be both an individual contributor and a technical mentor.
Job listings
Seeking a Machine Learning Engineer to join our advanced model development team, focusing on pre-training, continued training, and post-training of models, with emphasis on draft model optimization for speculative decoding and quantization-aware training (QAT). The ideal candidate has deep experience with training methodologies, open-weight models, and performance-tuning for inference.
Build AI systems that make finance simpler, smarter, and more inclusive. As a Machine Learning Engineer, you’ll develop and deploy models that power key features - from personalization and risk scoring to intelligent automation and fraud detection. Your work will have a direct and visible impact on millions of users across the region.
$216,700–$303,400
USD/year
Design, develop, and optimize graph-based ML models for large-scale recommendation systems. You will work on embedding generation, distributed training, and scalable serving architectures, playing a key role in improving Reddit’s AI-powered personalization. This role offers the opportunity to contribute to cutting-edge ML research and apply it at scale in a high-impact production environment.
Build and deploy ML models and tools that support personalization, automation, and insight generation, helping develop scalable ML infrastructure and pipelines, and integrating ML outputs into products and user-facing features. Work with product and data teams to define machine learning goals and strategies, handle data preprocessing, feature engineering, and model training/evaluation.
Work with product managers and stakeholders to define AI and machine learning objectives, requirements, and timelines. Design, develop, and implement AI models, algorithms, and applications to solve complex business challenges. Oversee the full AI model lifecycle, including data collection, preprocessing, model training, evaluation, and deployment.
Deliver GPU-powered AI/ML solutions for enterprise clients, focusing on implementation, integration, and optimization of production-grade systems. Integrate Nebius AI solutions into diverse client environments. Design and set up scalable ML training and inference workflows on GPU clusters. Automate MLOps pipelines and manage the entire model lifecycle. Develop clear architecture documentation and operational guides.
You’ll help build the intelligent systems that power this mission - from personalized recommendations and fraud detection to automation and search. You’ll join a fast-paced, flat team structure where your execution and ideas shape real-world outcomes every day. Your work will directly impact user experience, efficiency, and platform intelligence.
As an AI Engineer, you will work closely with Senior AI Engineers and MLOps/Data Engineers to develop, deploy, and optimize AI models that power our next-generation security products. This is a hands-on engineering role, requiring expertise in machine learning model development, deployment, and optimization. You will contribute to multiple AI initiatives, ensuring that models are efficient, scalable, and production-ready.
As a Machine Learning Engineer, you’ll develop and deploy models that power key features - from personalization and risk scoring to intelligent automation and fraud detection. Your work will have a direct and visible impact on millions of users across the region.