AI Algorithm Engineer

AI Algorithm Engineer Omni Solutions Services Arcadia, CA Job Details Full-time $80,000 - $150,000 a year 7 hours ago Benefits Health insurance Dental insurance 401(k) Paid time off Vision insurance Flexible schedule Retirement plan Qualifications GPU programming Data preprocessing PyTorch Computer vision Software coding Master's degree C++ Model deployment Model training Machine learning libraries AI Research & development Machine learning frameworks Generative AI Full Job Description Job Overview The company is seeking a highly skilled and passionate AI Algorithm Engineer to join the cutting-edge research and development team. Unlike standard applied AI roles, this position is deeply focused on the foundational layer of vision models. You will be instrumental in designing, pre-training, scaling, and fine-tuning our next-generation image foundation models from the ground up. You will not just be utilizing existing open-source models; you will be diving into the underlying architectures to create proprietary, state-of-the-art visual generation capabilities. If you are passionate about the complex mathematics of Diffusion models, the underlying architecture of Vision Transformers, and building robust, multi-modal systems that will directly power the core products, you are wanted to the team.

Duties:

Vision Foundation Model R D & Iteration:

Lead the underlying algorithm research, pre-training, and continuous optimization of cutting-edge image foundation models (e.g., Stable Diffusion, DiT, ViT, SAM, CLIP).

Business Scenario Customization & Fine-Tuning:

Tailor vision models to core business needs (such as AIGC image generation, image editing, and multi-modal understanding). Lead deep supervised fine-tuning (SFT) and parameter-efficient fine-tuning (e.g., LoRA, ControlNet, Adapters).

Model Architecture Innovation:

Explore and improve existing generative models and visual feature extraction network architectures to enhance image generation quality, stability, resolution, and cross-modal alignment.

Engineering Deployment & Performance Tuning:

Collaborate with the engineering team to implement end-to-end deployment of large models. Optimize inference performance and resolve engineering bottlenecks such as high VRAM usage and slow generation speeds (via inference acceleration, quantization, pruning, etc.).

Cutting-Edge Technology Tracking:

Continuously monitor the latest papers and open-source developments in Computer Vision (CV) and multi-modal large models, rapidly reproducing and translating state-of-the-art algorithms into business value.

Job Requirements Educational Background:

Master's degree or higher (Ph.D. preferred) in Computer Science, Artificial Intelligence, Applied Mathematics, or a related field. [Core Requirement] Deep Expertise in

Vision/Image Foundation Models:

Extensive R D experience with large vision models, possessing a deep understanding of the underlying architectures and mathematical principles of Diffusion Models, Vision Transformers (ViT), MAE, etc. Led or participated as a core member in the full pre-training lifecycle of vision or multi-modal models with hundreds of millions of parameters or more . Highly familiar with data cleaning strategies and ensuring training stability. Rich practical experience in Generative AI (AIGC), proficient in the underlying control and optimization technologies for Text-to-Image and Image-to-Image generation.

Coding & Framework Proficiency:

Solid programming foundations, proficient in Python and C++. Highly skilled in the PyTorch deep learning framework with excellent abilities in source code reading and secondary development.

Distributed Training Experience:

Familiar with large-scale cluster parallel training technologies (e.g., DeepSpeed, Megatron, FSDP), with hands-on experience in multi-node/multi-GPU distributed training tuning and compute resource management.

Bonus Points:

High-quality publications related to large vision models or generative models in top-tier academic conferences (e.g., CVPR, ICCV, ECCV, Neur

IPS, ICLR

). Active contributions to open-source communities (GitHub/Hugging Face) or top-ranking achievements in premier AI algorithms competitions (e.g., Kaggle). Experience with low-level operator optimization and High-Performance Computing (HPC) deployment, such as TensorRT and CUDA programming.

Pay:

$80,000.00 - $150,000.00 per year

Benefits:

401(k) Dental insurance Flexible schedule Health insurance Paid time off Retirement plan Vision insurance

Work Location:

Hybrid remote in Arcadia, CA 91007