位于上海市的 19 个优质deep learning engineer职位（正在招聘！）

Senior Applied Scientist, Large Language Models
PATSNAP —上海市
- 全职
22 小时
Senior Product Manager
Apple —上海市
AI Computing Software Development Engineer, TensorRT
NVIDIA —上海市
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Manager, Machine Learning, Customer Support Engineering
Airbnb —上海市
快速申请
Sen. Digital Solution Engineer. Special.
ABB Robotics (Shanghai) Investment Limited —上海市
快速申请
Senior AI Engineer (Python/ML)
EPAM Systems, Inc. —上海市
Data Engineer (Customer Analytics), IS&T Ai & Data Platforms
Apple —上海市
10天
GPU Kernel Development Engineer
Advanced Micro Devices, Inc —上海市
Applications Engineering, Staff Engineer - SI
Synopsys —上海市
AI Framework Eng.
Advanced Micro Devices, Inc —上海市
Software Engineer, AI and DL Kernel Libraries
NVIDIA —上海市
- 全职
P10K - Accenture - AI/ML Computational Science Manager
Accenture —上海市
- 全职
Senior Financial Analyst, Global Logistics, Global Logistic Finance
Beijing Century Joyo Courier Service Co., Ltd. —上海市
- 全职
12天
Validation / Verification Eng, Staff Engineer
Synopsys —上海市
Application Manager
Atlas Copco Group —上海市
Advisory Engineer, Google expert m/f/d
Lenovo —上海市
- 全职
Machine Learning Engineer, ML Infrastructure (New Grads)
Unity Software (Shanghai) Co., Ltd —上海市
Staff/ Senior Machine Learning Engineer, ML Infrastructure- Offline
Unity Software (Shanghai) Co., Ltd —上海市
10天
Staff/ Senior Machine Learning Engineer, ML Infrastructure- Online
Unity Software (Shanghai) Co., Ltd —上海市

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Senior Applied Scientist, Large Language Models

PATSNAP -
上海市

立即申请

职位详情

全职
22 小时前

完整职位描述

We are looking for a Senior Applied Scientist to develop advanced large language model capabilities for complex, knowledge-intensive applications.

You will work across applied research, model development, evaluation, and product implementation. The role requires both strong algorithmic foundations and the ability to translate emerging AI technologies into reliable, scalable product capabilities.

You will collaborate closely with engineering, product, data, and domain teams to identify high-value algorithmic problems and drive solutions from experimentation to production.

Key Responsibilities

Research and develop large language model capabilities for real-world applications.
Improve model performance in areas such as reasoning, long-context understanding, information extraction, retrieval-augmented generation, and domain adaptation.
Design and implement model post-training approaches, including supervised fine-tuning, preference optimization, knowledge distillation, and synthetic data generation.
Develop systematic evaluation methodologies covering accuracy, factuality, robustness, safety, latency, and cost.
Build scalable data preparation, model experimentation, and evaluation pipelines.
Analyse model failure cases and identify effective approaches for continuous improvement.
Explore emerging research and assess its practical value in production environments.
Work with engineering teams to deploy and optimize models and AI capabilities in production.
Collaborate with product managers and domain experts to translate business requirements into algorithmic solutions.
Contribute to technical standards, best practices, and the longer-term development of the AI technology roadmap.
Provide technical guidance and support to other algorithm engineers and researchers.

Qualifications

Master’s degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, Natural Language Processing, or a related discipline, or equivalent practical experience.
Strong experience in machine learning, natural language processing, or applied AI.
Hands-on experience developing or adapting large language models.
Strong understanding of Transformer architectures, model training, fine-tuning, and inference.
Practical experience in at least two of the following areas:
- LLM post-training and alignment
- Model evaluation and benchmarking
- Retrieval-augmented generation
- Long-context modelling
- Information extraction
- Complex reasoning and planning
- Model compression or inference optimization
Strong proficiency in Python and deep learning frameworks such as PyTorch.
Ability to independently define algorithmic problems, design experiments, analyse results, and deliver production-ready solutions.
Strong communication and cross-functional collaboration skills.

Preferred Qualifications

Experience developing AI solutions for enterprise, scientific, technical, or other knowledge-intensive applications.
Experience with distributed training, large-scale inference, or GPU optimization.
Experience building automated evaluation systems, data flywheels, or human-feedback pipelines.
Experience with multimodal models, AI agents, or tool-augmented language models.
Publications in reputable AI, machine learning, or NLP conferences, or meaningful open-source contributions.

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在上海市的deep learning engineer个职位

Senior Applied Scientist, Large Language Models

Senior Product Manager

AI Computing Software Development Engineer, TensorRT

Manager, Machine Learning, Customer Support Engineering

Sen. Digital Solution Engineer. Special.

Senior AI Engineer (Python/ML)

Data Engineer (Customer Analytics), IS&T Ai & Data Platforms

GPU Kernel Development Engineer

Applications Engineering, Staff Engineer - SI

AI Framework Eng.

Software Engineer, AI and DL Kernel Libraries

P10K - Accenture - AI/ML Computational Science Manager

Senior Financial Analyst, Global Logistics, Global Logistic Finance

Validation / Verification Eng, Staff Engineer

Application Manager

Advisory Engineer, Google expert m/f/d

Machine Learning Engineer, ML Infrastructure (New Grads)

Staff/ Senior Machine Learning Engineer, ML Infrastructure- Offline

Staff/ Senior Machine Learning Engineer, ML Infrastructure- Online

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