Senior / Staff Computer Vision & AI Algorithm Engineer (Core R&D)

Jabil; Singapore; On-site; SGD 120,000 - 170,000; Full time

Job summary

Jabil in Singapore seeks a core algorithm R&D engineer to advance our internally developed vision platform. You will drive state-of-the-art computer vision, deep learning, and multimodal model techniques for industrial-grade performance and robustness.

You will develop high-performance training/inference pipelines using Python/C++, PyTorch, CUDA, and vectorized code. Collaboration with cross-functional teams is essential to ship reliable AI features.

Qualifications

• Bachelor’s / Master’s / PhD in Computer Science, Electrical Engineering, Applied Mathematics, or related fields (industry experience may substitute).
• Strong fundamentals and hands-on experience in deep learning for computer vision, including detection and segmentation.
• Solid engineering ability with Python + C++; capable of building clean training code (with PyTorch) and production-ready modules.
• Practical experience with performance optimization and acceleration (CUDA / SIMD / parallel computing).
• Ability to communicate effectively in both Chinese (Mandarin) and English.

Responsibilities

• Core Vision Algorithm R&D (Deep Learning + Transformers): research, develop, and optimize CV algorithms including CNN-based and Transformer-based detection/recognition architectures; design evaluation protocols and ablation studies.
• Few-shot / Small-sample Learning for Industrial Use Cases: own R&D for few-shot rotated detection, segmentation, and anomaly detection; explore meta-learning and foundation-model feature adaptation.
• LLM / VLM Fine-tuning & Reinforcement Learning (Post-training): implement supervised and PEFT fine-tuning, alignment methods, and reproducible training workflows.
• Vector / Graph-based Learning for CAD/PCB & Structured Data: study models beyond raster images, apply GNNs and vector representations for component understanding and connectivity reasoning.
• High-performance Implementation & Productionization: write efficient C++/Python code for training/inference; optimize CUDA/SIMD kernels; ensure integration with product modules.
• Paper Reading & Reproducibility: read top-tier papers, reproduce core algorithms, deliver technical notes.

Skills

Deep learning for CV

Python

C++

Transformer-based architectures

Few-shot learning

Multimodal models

English & Mandarin communication

Education

Bachelor/Master/PhD in CS/EE/Math

Tools

PyTorch

CUDA

SIMD

GNNs

Vector data representations

Job description

At Jabil (NYSE: JBL), we are proud to be a trusted partner for the world’s top brands, offering comprehensive engineering, supply chain, and manufacturing solutions. With 60 years of experience across industries and a vast network of over 100 sites worldwide, Jabil combines global reach with local expertise to deliver both scalable and customized solutions. Our commitment extends beyond business success as we strive to build sustainable processes that minimize environmental impact and foster vibrant and diverse communities around the globe.

Job Summary

We are hiring a core algorithm R&D engineer to develop and advance the key AI capabilities of our internally developed vision platform. You will drive research-to-production delivery ofstate-of-the-art computer 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-based classification, anomaly detection, Siamese networks, object detection, rotated object detection , semantic segmentation, instance segmentation,keypointdetection.
• Build and improve Transformer-based detection/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 for few-shot rotated detection, segmentation, and anomaly detection—aiming to train effective models from only 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 for vector data scenarios (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 in C++ and Python for training/inference pipelines and algorithm modules.
• Develop high-performancecomputekernels and optimizations using SIMD and/or CUDA , 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

• Bachelor’s / Master’s / PhD in Computer Science, Electrical Engineering, Applied Mathematics, or related fields (industry experience may substitute).
• Strong fundamentals and hands-on experience in deep learning for computer vision , including detection and segmentation.
• Solid engineering ability with Python + C++ ; capable of building clean training code（with Pytorch )and production-ready modules.
• Practical experience with performance optimization and acceleration (one or more of CUDA / SIMD / parallel computing ).
• Ability to communicate effectively in both Chinese** (Mandarin)and English** as the successful person will have to liaise with our counterparts in China.

Jabil, including its subsidiaries, is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, age, disability, genetic information, veteran status, or any other characteristic protected by law.

Accessibility Accommodation

If you are a qualified individual with a disability, you have the right to request a reasonable accommodation if you are unable or limited in your ability to use or access Jabil.com/Careers site as a result of your disability. You can request a reasonable accommodation by sending an e-mail to [e-mail] with the nature of your request and contact information. Please do not direct any other general employment related questions to this e-mail. Please note that only those inquiries concerning a request for reasonable accommodation will be responded to.

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