Senior Algorithm Engineer (World Model)

Beijing Foreign Enterprise Management Consultants Co.,Ltd.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Huawei in Singapore seeks a Senior Algorithm Engineer specializing in large vision-language generation models for autonomous driving and embodied intelligence. You will push research boundaries, design advanced simulation systems, and apply state-of-the-art generative techniques to complex, real-time scenarios.

You will collaborate with cross-functional teams to refine algorithms, validate models, and deliver robust simulation-powered solutions that scale across platforms and deployments.

Qualifications

• Master's degree or above in Computer Science, AI, Robotics, or related field.
• 1–5 years of research or development experience in generative AI, 3D/4D reconstruction, or multimodal LLMs.
• Proficiency in PyTorch or TensorFlow and solid implementation skills.
• Experience with large-scale autonomous driving data and multi-modal sensor data is a plus.

Responsibilities

• Conduct cutting-edge algorithm research and system development for world models targeting autonomous driving and embodied intelligence.
• Design, build, and optimize closed-loop simulation systems enabling multi-module collaboration across simulation, rendering, and planning/control.
• Leverage video generation and 4D reconstruction techniques to study world model methods for large-scale simulation.
• Track latest advances in world models, generative simulation, reinforcement learning, and apply them to optimize pipelines.
• Ensure stable delivery of algorithmic capabilities into simulation platforms or productized solutions.

Job description

On behalf of Huawei, a world-renowned information and communication technology company, we are seeking passionate and talented individuals to join our team as Senior Algorithm Engineer (Large Vision-Language Generation Model)

Job Responsibilities:

• Conduct cutting-edge algorithm research and system development for world models targeting autonomous driving and embodied intelligence, with a focus on end-to-end closed-loop simulation. Responsibilities include, but are not limited to: requirement analysis of algorithmic subsystems, conceptual modelling, data collection and construction, model design, training, and validation, as well as identifying and resolving critical algorithmic and system-level challenges;
• Design, build, and optimize closed-loop simulation systems, enabling multi-module collaboration across simulation, rendering, and planning/control, and improving the simulation environment in terms of temporal consistency, multi-view consistency, physical plausibility, interaction controllability, and long-horizon sequence generation;
• Leverage technologies related to video generation and 4D reconstruction/generation to study world model methods with capabilities such as generation, rollout, and counterfactual reasoning, supporting large-scale simulation for training and evaluation in autonomous driving and embodied intelligence tasks;
• Continuously track and incorporate the latest advances from academia and industry in areas including world models, generative simulation, reinforcement learning, planning and decision-making, and apply them to optimize existing simulation and algorithm pipelines;
• Ensure the stable delivery of algorithmic capabilities into simulation platforms, training systems, or productized solutions, while exploring new application scenarios and deployment opportunities based on emerging technology trends.

Job Requirements:

• Master's degree or above in Computer Science, Artificial Intelligence, Robotics, or related engineering fields (PhD preferred);
• 1-5 years of research or development experience in relevant areas, including but not limited to: generative AI (image, video, 3D/4D), 3D/4D reconstruction, multimodal large language models, reinforcement learning, and embodied intelligence. First-author publications in top-tier conferences or journals are a strong plus, such as CVPR, ICCV, ECCV, SIGGRAPH, ICLR, NeurIPS, CoRL, RSS, etc.;
• Proficiency in at least one mainstream deep learning framework (e.g., PyTorch or TensorFlow), with solid algorithm implementation and experimental skills; familiarity with generative models such as Diffusion, VAE, and Autoregressive Models;
• Experience in large-scale autonomous driving data processing and analysis is a plus; familiarity with the construction and usage of multi-modal sensor data (e.g., cameras, LiDAR, trajectories, and behaviour logs) is preferred. Experience with autonomous driving or embodied intelligence simulation platforms is also a plus (e.g., CARLA, Isaac Sim, MuJoCo, Unity, UE, etc.);
• Strong ability for independent thinking and research-driven development, with a collaborative mindset and willingness to work closely with cross-functional teams.