招聘
必备技能
Python
SQL
AWS
Git
Airflow
Role Overview We are seeking a highly skilled Data Scientist to design, develop and deploy advanced AI solutions leveraging cutting-edge Generative AI technology.
The candidate should have hands-on experience in building Generative AI solutions using various Large Language Models, techniques such as RAG, Agentic AI and demonstrate expertise in querying and transforming structured datasets.
Proficiency in AWS cloud deployment is essential, ensuring scalable and secure AI solutions for enterprise applications.
Key Responsibilities Gen AI Development:
Using and fine-tune generative AI models (LLMs, diffusion models, GANs, etc.) for text, image, and multimodal applications.
Built Gen AI solutions using Lang Chain, Lang Graph for essential tasks like Chunking, Vectorization & Retrieval using Vector DB, Knowledge Augmentation using RAG and Agentic AI.
Structured Data Querying & Processing: Develop robust data pipelines for structured data sources (SQL/NoSQL databases, data warehouses).
Write efficient queries and transformations for large-scale datasets, ensuring data quality and consistency for downstream AI/ML tasks. ML Engineering: Design, implement, and maintain robust ML pipelines for data ingestion, model training, validation, deployment, and monitoring.
Automate workflows using CI/CD tools, manage experiment tracking, and facilitate model versioning and rollback strategies.
Feature Engineering: Prepare and preprocess large datasets for training and evaluation.
Model Evaluation: Implement Observability of the AI solutions using tools like Lang Smith, MLflow and monitor performance metrices to analyze performance and plan for enhancements Cloud Deployment: Deploy AI models on AWS services (Sage Maker, Lambda, ECS, EKS) ensuring high availability and performance.
Optimization: Implement model compression, inference optimization, and cost-efficient deployment strategies.
DevOps & MLOps: Develop automated pipelines for training, testing, and deployment using AWS & Git Workflow CI/CD tools.
Identify retraining phase of AI models based on Model/Data/Concept Drift indicators.
Research & Innovation: Stay updated on the latest advancements in generative AI and integrate them into business solutions.
Collaboration: Work closely with the stakeholders to deliver AI-driven features.
Required Skills Strong proficiency in Python, Lang Chain, Lang Graph, Lang Smith, Sci Kit, Numpy, Pandas.
Expertise in Generative AI techniques (LLMs, transformers, diffusion models, GANs, RAG, Agentic AI).
Hands-on experience with AWS services: Sage Maker, EC2, S3, Lambda, EKS/ECS, API Gateway, Bedrock.
Experience: with MLOps frameworks (Kubeflow, MLflow, Airflow) and automated ML pipelines.
Familiarity with API development, microservices architecture and data security best practices.
Strong understanding of data security and cloud best practices.
Strong understanding of cloud best practices and cost optimisation.
Preferred Qualifications:
Experience: with prompt engineering and fine-tuning LLMs.
Knowledge of distributed training and GPU optimization.
Publications or contributions in AI research communities.
Education: Bachelor’s/master’s in computer science, Data Science, AI/ML or related field.
Let us learn about you!
Apply today.
You must submit an online application to be considered for any position with us.
This position will be posted until filled.
Looking to make an IMPACT with your career?
When you are thinking about joining a new team, culture matters.
At Schneider Electric, our values and behaviors are the foundation for creating a great culture to support business success.
We believe that our IMPACT values – Inclusion, Mastery, Purpose, Action, Curiosity, Teamwork – starts with us. IMPACT is also your invitation to join Schneider Electric where you can contribute to turning sustainability ambition into actions, no matter what role you play.
It is a call to connect your career with the ambition of achieving a more resilient, efficient, and sustainable world.
We are looking for IMPACT Makers; exceptional people who turn sustainability ambitions into actions at the intersection of automation, electrification, and digitization.
We celebrate IMPACT Makers and believe everyone has the potential to be one.
Become an IMPACT Maker with Schneider Electric – apply today! €36 billion global revenue +13% organic growth 150 000+ employees in 100+ countries #1 on the Global 100 World’s most sustainable corporations You must submit an online application to be considered for any position with us.
This position will be posted until filled.
Schneider Electric aspires to be the most inclusive and caring company in the world, by providing equitable opportunities to everyone, everywhere, and ensuring all employees feel uniquely valued and safe to contribute their best.
We mirror the diversity of the communities in which we operate, and ‘inclusion’ is one of our core values.
We believe our differences make us stronger as a company and as individuals and we are committed to championing inclusivity in everything we do.
At Schneider Electric, we uphold the highest standards of ethics and compliance, and we believe that trust is a foundational value.
Our Trust Charter is our Code of Conduct and demonstrates our commitment to ethics, safety, sustainability, quality and cybersecurity, underpinning every aspect of our business and our willingness to behave and respond respectfully and in good faith to all our stakeholders.
You can find out more about our Trust Charter here Schneider Electric is an Equal Opportunity Employer.
It is our policy to provide equal employment and advancement opportunities in the areas of recruiting, hiring, training, transferring, and promoting all qualified individuals regardless of race, religion, color, gender, disability, national origin, ancestry, age, military status, sexual orientation, marital status, or any other legally protected characteristic or conduct.
Role Overview We are seeking a highly skilled Data Scientist to design, develop and deploy advanced AI solutions leveraging cutting-edge Generative AI technology.
The candidate should have hands-on experience in building Generative AI solutions using various Large Language Models, techniques such as RAG, Agentic AI and demonstrate expertise in querying and transforming structured datasets.
Proficiency in AWS cloud deployment is essential, ensuring scalable and secure AI solutions for enterprise applications.
Key Responsibilities Gen AI Development:
Using and fine-tune generative AI models (LLMs, diffusion models, GANs, etc.) for text, image, and multimodal applications.
Built Gen AI solutions using Lang Chain, Lang Graph for essential tasks like Chunking, Vectorization & Retrieval using Vector DB, Knowledge Augmentation using RAG and Agentic AI.
Structured Data Querying & Processing: Develop robust data pipelines for structured data sources (SQL/NoSQL databases, data warehouses).
Write efficient queries and transformations for large-scale datasets, ensuring data quality and consistency for downstream AI/ML tasks. ML Engineering: Design, implement, and maintain robust ML pipelines for data ingestion, model training, validation, deployment, and monitoring.
Automate workflows using CI/CD tools, manage experiment tracking, and facilitate model versioning and rollback strategies.
Feature Engineering: Prepare and preprocess large datasets for training and evaluation.
Model Evaluation: Implement Observability of the AI solutions using tools like Lang Smith, MLflow and monitor performance metrices to analyze performance and plan for enhancements Cloud Deployment: Deploy AI models on AWS services (Sage Maker, Lambda, ECS, EKS) ensuring high availability and performance.
Optimization: Implement model compression, inference optimization, and cost-efficient deployment strategies.
DevOps & MLOps: Develop automated pipelines for training, testing, and deployment using AWS & Git Workflow CI/CD tools.
Identify retraining phase of AI models based on Model/Data/Concept Drift indicators.
Research & Innovation: Stay updated on the latest advancements in generative AI and integrate them into business solutions.
Collaboration: Work closely with the stakeholders to deliver AI-driven features.
Required Skills Strong proficiency in Python, Lang Chain, Lang Graph, Lang Smith, Sci Kit, Numpy, Pandas.
Expertise in Generative AI techniques (LLMs, transformers, diffusion models, GANs, RAG, Agentic AI).
Hands-on experience with AWS services: Sage Maker, EC2, S3, Lambda, EKS/ECS, API Gateway, Bedrock.
Experience: with MLOps frameworks (Kubeflow, MLflow, Airflow) and automated ML pipelines.
Familiarity with API development, microservices architecture and data security best practices.
Strong understanding of data security and cloud best practices.
Strong understanding of cloud best practices and cost optimisation.
Preferred Qualifications:
Experience: with prompt engineering and fine-tuning LLMs.
Knowledge of distributed training and GPU optimization.
Publications or contributions in AI research communities.
Education: Bachelor’s/master’s in computer science, Data Science, AI/ML or related field.
Let us learn about you!
Apply today.
You must submit an online application to be considered for any position with us.
This position will be posted until filled.
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关于Schneider Electric

Schneider Electric
PublicSchneider Electric SE is a French multinational corporation that specializes in energy technology, covering electrification, automation, and digitalization for industry and homes.
10,001+
员工数
Rueil-Malmaison
总部位置
$25B
企业估值
评价
3.8
10条评价
工作生活平衡
3.2
薪酬
4.0
企业文化
4.1
职业发展
3.5
管理层
3.4
72%
推荐给朋友
优点
Great company culture and team environment
Good benefits and compensation
Flexibility and work accommodations
缺点
Upper management issues and lack of support
Enforcement of in-person work policies
Limited PTO and hiring freezes
薪资范围
14个数据点
Mid/L4
Principal/L7
Senior/L5
Mid/L4 · DATA INTELLIGENCE ANALYST
1份报告
$117,000
年薪总额
基本工资
$90,645
股票
-
奖金
-
$117,000
$117,000
面试经验
1次面试
难度
3.0
/ 5
时长
14-28周
录用率
100%
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Interview
4
Hiring Manager Interview
5
Offer
常见问题
Technical Knowledge
Behavioral/STAR
Past Experience
Problem Solving
Culture Fit
新闻动态
The 10 Most Influential Energy Companies of 2026 - Time Magazine
Time Magazine
News
·
3d ago
Schneider Electric appoints Kelly Becker as President of North America Operations - marketscreener.com
marketscreener.com
News
·
3d ago
General experience trying to use Cowork. As an example, trying to use the career-ops-plugin.
I was unclear on the instructions "Install \# Local development claude --plugin-dir ./career-ops-plugin \# Or clone into your plugins directory git clone [https://github.com/andrewshwetzer/career-ops-plugin.git](https://github.com/andrewshwetzer/career-ops-plugin.git)" So I asked Claude Cowork how to do this. It said any Cowork plugins folder is hidden and obfuscated from user view, and not inteded for user intervention. I asked it how to take this Github project and install it. It did va
·
4d ago
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2
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2
A Look At Schneider Electric’s (ENXTPA:SU) Valuation After The TeSys Tera Motor Management Launch - Yahoo Finance
Yahoo Finance
News
·
5d ago