
Global investment banking and financial services
Machine Learning Engineer Vice President
必备技能
Python
SQL
Docker
Kubernetes
Machine Learning
We are seeking a highly skilled and motivated Machine Learning Engineer to join our technology team. The ideal candidate will be responsible for designing, developing, and deploying cutting-edge applications that leverage Generative AI and Large Language Models (LLMs). This role involves architecting end-to-end platform services with a focus on scalability, reliability, and performance. You will be a key player in driving the implementation of new AI-driven systems and programs that will impact all business line at Citi globally.
Responsibilities
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Architect and Build AI Solutions: Design and architect end-to-end platform capabilities and services that integrate with Generative AI technologies.
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Implement RAG Solutions: Develop and deploy solutions using VectorRAG and GraphRAG techniques with both open-source and commercial Large Language Models.
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Develop AI Workflows: Apply a strong understanding of Agentic AI workflows and frameworks to build sophisticated, automated systems.
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Drive DevOps Best Practices: Implement robust CI/CD pipelines, automated testing, and containerization (Docker, Kubernetes) to streamline the development and deployment of machine learning models.
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End-to-End Project Ownership: Manage your deliverables from conception to deployment, proactively identifying and mitigating risks to ensure project goals are met.
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Rapid Prototyping: Perform and lead quick proof-of-concept (POC) projects to evaluate and demonstrate the feasibility of new GenAI use cases.
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Ensure System Integrity: Appropriately assess and manage risk in all technical and business decisions, ensuring compliance with applicable laws, rules, and regulations, and maintaining transparency in reporting and managing control issues.
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Collaborate and Innovate: Work closely with cross-functional teams to solve complex problems, adapt quickly to changing priorities, and contribute to a culture of innovation.
Required Qualifications
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Experience: 5+ years of relevant experience in Software Development or a Systems Analysis role, with a strong focus on machine learning.
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Programming Skills: Strong object-oriented programming skills with expert-level proficiency in Python.
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AI/ML Expertise: Deep experience with AI/ML frameworks (e.g., Langchain) and hands-on experience with Generative AI technologies and Large Language Models.
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Application Development: Proven experience building applications that apply LLMs and GenAI to use cases such as search, chat agents, and guided analytics.
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DevOps Knowledge: Strong, working knowledge of DevOps tools (e.g., Jenkins, GitLab, Docker, Kubernetes) and Infrastructure as Code (IaC) practices.
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Architectural Understanding: Solid understanding of modern software development practices, including microservices architecture and API design principles.
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Data Proficiency: Experience with various data storage solutions (e.g., NoSQL, SQL, data lakes) and data pipeline orchestration.
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Problem-Solving: Excellent analytical and problem-solving skills with a proven ability to troubleshoot complex technical issues and provide innovative solutions.
Education:
Bachelor's Degree in Computer Science, Computer Engineering, Information Systems or equivalent work experience
Desired Skills
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Cloud Architecture: Experience with various cloud platforms (e.g., AWS, GCP, Azure) and architectures (e.g., single/multi-tenant).
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Large-Scale Systems: Experience designing and implementing microservices-based architectures for large-scale platforms in complex environments.
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Leadership: Demonstrated leadership, project management skills, and a proven track record of self-motivation and continuous learning.
Job Family Group:
Technology
Job Family:
Applications Development
Time Type:
Full time
Primary Location:
Jersey City New Jersey United States:
Primary Location Full Time Salary Range:
$142,320.00 - $213,480.00
In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.
Most Relevant Skills:
Please see the requirements listed above.
Other Relevant Skills
AI Frameworks, Generative AI, Large Language Model (LLM) Fine-Tuning, ML Frameworks, Python (Programming Language).
Anticipated Posting Close Date:
Mar 16, 2026
Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.
If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.
View Citi’s EEO Policy Statement and the Know Your Rights poster.
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关于Citigroup

Citigroup
PublicCitigroup Inc. or Citi is an American multinational investment bank and financial services company based in New York City. The company was formed in 1998 by the merger of Citicorp, the bank holding company for Citibank, and Travelers; Travelers was spun off from the company in 2002.
10,001+
员工数
New York City
总部位置
$86B
企业估值
评价
10条评价
3.7
10条评价
工作生活平衡
3.8
薪酬
2.5
企业文化
4.0
职业发展
3.2
管理层
3.5
65%
推荐率
优点
Good work-life balance
Supportive management and colleagues
Good benefits
缺点
Low or uncompetitive salary/pay
Long hours during peak times
Poor management and lack of direction
薪资范围
48个数据点
Mid/L4
Senior/L5
Mid/L4 · BUSINESS ANALYTICS SENIOR ANALYST
3份报告
$117,000
年薪总额
基本工资
$120,800
股票
-
奖金
-
$117,000
$117,000
面试评价
3条评价
难度
3.3
/ 5
时长
14-28周
体验
正面 0%
中性 33%
负面 67%
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Interview
4
Panel/Group Interview
5
Final Round
6
Offer
常见问题
Technical Knowledge
Coding/Algorithm
Behavioral/STAR
Past Experience
Culture Fit
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