位于上海市的 18 个优质machine learning engineer职位（正在招聘！）

Senior Applied Scientist, Large Language Models
PATSNAP —上海市
- 全职
1天
Sr. Software System Engineer
Corning —上海市
6天
Software Engineer, AI and DL Kernel Libraries
NVIDIA —上海市
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Apple —上海市
5天
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Roche —上海市
- 实习
汽车软件与AI解决方案销售_ETAS
Bosch Group —上海市
快速申请
Senior AI Engineer (Python/ML)
EPAM Systems, Inc. —上海市
Software Engineer - Athena Synapse, IS&T Ai & Data Platforms
Apple —上海市
5天
P10K - Accenture - AI/ML Computational Science Manager
Accenture —上海市
- 全职
Software Dev Engineer Intern, (Sustaining Operations) 2026 Shanghai
Amazon (China) Holding Company Limited —上海市
- 全职
Senior Manager-AI Algorithm
AstraZeneca —上海市
2天
Learning-based Planning and Prediction Research Scientist for Autonomous Driving_CR
Bosch Group —上海市
快速申请
Software Dev Engineer Intern, (Manufacturing&Ops) 2026 Shanghai
Amazon (China) Holding Company Limited —上海市
- 全职
Software Dev Engineer Intern, OpenSearch, 2026 Shanghai
Amazon (China) Holding Company Limited —上海市
- 全职
Machine Learning Engineer, ML Infrastructure (New Grads)
Unity Software (Shanghai) Co., Ltd —上海市
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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
Senior Machine Learning Engineer
Qualcomm —上海市
2 小时

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Senior Applied Scientist, Large Language Models

PATSNAP -
上海市

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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.

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在上海市的machine learning engineer个职位

Senior Applied Scientist, Large Language Models

Sr. Software System Engineer

Software Engineer, AI and DL Kernel Libraries

Data Engineer, IS&T Ai & Data Platforms

Data Scientist Intern

汽车软件与AI解决方案销售_ETAS

Senior AI Engineer (Python/ML)

Software Engineer - Athena Synapse, IS&T Ai & Data Platforms

P10K - Accenture - AI/ML Computational Science Manager

Software Dev Engineer Intern, (Sustaining Operations) 2026 Shanghai

Senior Manager-AI Algorithm

Learning-based Planning and Prediction Research Scientist for Autonomous Driving_CR

Software Dev Engineer Intern, (Manufacturing&Ops) 2026 Shanghai

Software Dev Engineer Intern, OpenSearch, 2026 Shanghai

Machine Learning Engineer, ML Infrastructure (New Grads)

Staff/ Senior Machine Learning Engineer, ML Infrastructure- Offline

Staff/ Senior Machine Learning Engineer, ML Infrastructure- Online

Senior Machine Learning Engineer

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