位于上海市的 4 个优质deep learning engineer职位（正在招聘！）

Senior Applied Scientist, Large Language Models
PATSNAP —上海市
- 全职
1天
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
11天
Staff/ Senior Machine Learning Engineer, ML Infrastructure- Online
Unity Software (Shanghai) Co., Ltd —上海市

Related jobs to explore

Based on your search for deep learning engineer

全球管理培训生-数据与人工智能-上海
Merck KGaA —上海市
Strong interest in AI, machine learning, data engineering and analysis. During this 24-months program you will be taking an active part in our data & AI-driven,…
Senior Software Engineer, Test Frameworks
Apple —上海市
A passion for product quality and a strong aptitude for learning new technologies, along with a good instinct for discovering defects in software and hardware.

Show more related jobs

我想收到关于上海市的 deep learning engineer 的最新职位提醒

一旦登录您的账户，即表明您同意 SimplyHired 的服务条款和我们的Cookie 协议及隐私政策。

查看更多地区的职位

deep learning engineer jobs near 上海市

位于上海市的Machine Learning Engineer职位

位于上海市的Engineer 产品工程师职位

位于北京市的Technical Support Engineer职位

位于江苏省的Senior Engineer职位

位于苏州市的Senior Operations Manager职位

位于上海市的Senior Logistics职位

Senior Applied Scientist, Large Language Models

PATSNAP -
上海市

立即申请

职位详情

全职
1 天前

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.

立即申请

完善您的搜索

在上海市的deep learning engineer个职位

Senior Applied Scientist, Large Language Models

Machine Learning Engineer, ML Infrastructure (New Grads)

Staff/ Senior Machine Learning Engineer, ML Infrastructure- Offline

Staff/ Senior Machine Learning Engineer, ML Infrastructure- Online

Related jobs to explore

我想收到关于上海市的 deep learning engineer 的最新职位提醒

Related Searches

查看更多地区的职位

Key Responsibilities

Qualifications

Preferred Qualifications

求职者工具

雇主工具

浏览

保持联系

完善您的搜索

在上海市的deep learning engineer个职位

Machine Learning Engineer, ML Infrastructure (New Grads)

Staff/ Senior Machine Learning Engineer, ML Infrastructure- Offline

Staff/ Senior Machine Learning Engineer, ML Infrastructure- Online

Related jobs to explore

我想收到关于 上海市 的 deep learning engineer 的最新职位提醒

Related Searches

查看更多地区的职位

Key Responsibilities

Qualifications

Preferred Qualifications

我想收到关于上海市的 deep learning engineer 的最新职位提醒