Job Summary

We are hiring acore algorithm R&D engineerto develop and advance the key AI capabilities of ourinternally developed vision platform. You will drive research-to-production delivery ofstate-of-the-artcomputer vision deep learning and multimodal foundation model techniques focusing on industrial-grade performance robustness and efficiency.

Key Responsibilities

Core Vision Algorithm R&D (Deep Learning Transformers)

• Research develop and optimize computer vision algorithms across:
  CNN-basedclassification anomaly detection Siamese networks object detectionrotated object detection semantic segmentation instance segmentationkeypointdetection.

• Build and improveTransformer-baseddetection/recognition architectures and training pipelines.

• Design evaluation protocols run ablation studies and iterate based on measurable improvements (accuracy robustness latency).

Few-shot / Small-sample Learning for Industrial Use Cases

• Own R&D forfew-shotrotated detection segmentation and anomaly detectionaiming to train effective models fromonly a few images.

• Explore and implement methods such as meta-learning prompt-/prototype-based learning retrieval-enhanced approaches and foundation-model feature adaptation for industrial inspection scenarios.

LLM / VLM Fine-tuning & Reinforcement Learning (Post-training)

• Understand LLM/VLM principles and implement practical post-training pipelines:

• Supervised fine-tuning(SFT) parameter-efficient fine-tuning (e.g.LoRA/PEFT) alignment methods (e.g. RLHF/DPO-like approaches) evaluationharnessesand safety/quality checks.

• Build reproducible training workflows (data curation experiment tracking model versioning deployment readiness).

Vector / Graph-based Learning for CAD/PCB & Structured Data

• Research and develop models beyond raster images forvector datascenarios (e.g. engineering drawings PCB schematics/layouts) aiming to outperform image-based baselines.

• Applygraph neural networks(GNNs)and vector/geometric representations to tasks such as component understanding connectivity reasoning and structured recognition.

High-performance Implementation &Productionization

• Write efficient maintainable code inC and Pythonfor training/inference pipelines and algorithm modules.

• Develop high-performancecomputekernels and optimizations usingSIMDand/orCUDA profiling and improving runtime memory use and throughput.

• Collaborate with platform/software teams to integrate algorithms into product modules and ensure test coverage stability and maintainability.

Paper Reading & Reproducibility

• Regularly read and analyze top-tier papers;identifykey contributions and reproduce core algorithms in code.

• Deliver internal technical notes and share learnings with the team.

Required Qualifications

• Bachelors / Masters / PhD in Computer Science Electrical Engineering Applied Mathematics or related fields (industry experience may substitute).

• Strong fundamentals and hands-on experience indeep learning for computer vision including detection and segmentation.

• Solid engineering ability withPython C; capable of building clean training codewithPytorch)and production-ready modules.

• Practical experience with performance optimization and acceleration (one or more ofCUDA / SIMD / parallel computing).

• Ability to communicate effectively inboth Chinese(Mandarin)and English as the successful person will have to liaise with our counterparts in China.