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Senior Machine Learning Engineer, Vice President

at Citi

Back to all Data Science / AI / ML jobs
Citi logo
Industry not specified

Senior Machine Learning Engineer, Vice President

at Citi

Mid LevelNo visa sponsorshipData Science/AI/ML

Posted 9 hours ago

No clicks

Compensation
$125,600 – $188,400 USD

Currency: $ (USD)

City
Tampa
Country
United States

Lead the design, architecture, and deployment of scalable machine learning systems, including advanced NLP and Generative AI (LLM) solutions, across Citi platforms. Own the end-to-end ML lifecycle in production—from deployment to monitoring and retraining—driving performance, reliability, and scalability. Provide technical leadership and mentorship, conducting code reviews and collaborating with data scientists, product managers, and other engineering teams to translate complex business requirements into robust ML solutions while considering risk and regulatory compliance.

Senior Machine Learning Engineer, Vice President

Job Req Id:
26942580
Location(s):
Tampa, Florida, United States
Job Type:
Hybrid
Posted:
Mar. 04, 2026

Discover your future at Citi

Working at Citi is far more than just a job. A career with us means joining a team of more than 230,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.

Job Overview

Candidate should possess deep hands-on expertise in designing, building, and deploying scalable machine learning systems, including advanced NLP and Generative AI (LLM) solutions. This position demands strong technical leadership, a quick learning ability, a proven track record in delivering high-value, production-grade AI solutions, and the capacity to mentor junior engineers.

The right candidate will be expected to be a key player in the project evolution & deployment shouldering the following responsibilities:

Work as a collaborative member of a team spread over multiple locations (India, UK, US) Understand internally published architectural guidelines to design solutions and represent them in architectural reviews. Define & communicate development standards that follow established architectural designs and perform code reviews to ensure quality standards of systems & team. Lead by example in developing exceptional quality code by doing design & code reviews. Design & develop platform functionality that is scalable & configurable as a global platform.

Key Responsibilities

  • ML System Design & Architecture: Lead the design and architecture of robust, scalable, and high-performance machine learning systems, ensuring seamless integration with existing platforms.
  • Production ML Model Deployment: Own the end-to-end lifecycle of deploying and operationalizing machine learning models in production environments, ensuring efficiency, reliability, and maintainability.
  • Advanced AI/ML Engineering: Develop, optimize, and implement advanced machine learning algorithms and statistical models, focusing on engineering best practices for performance and scalability.
  • Generative AI & NLP System Development: Engineer and integrate cutting-edge Generative AI (LLM) and Natural Language Processing (NLP) solutions. This includes designing efficient prompting strategies, developing LLM-based data augmentation techniques, and implementing Retrieval-Augmented Generation (RAG, including advanced RAG) to enhance model capabilities within production systems.
  • Deep Learning Infrastructure: Design and build systems to effectively apply and deploy deep learning techniques (ANN, LSTM, CNN, BERT, XLNet, Transformers, neural & LLM-based embeddings) for state-of-the-art AI applications at scale.
  • MLOps & Automation: Establish and implement MLOps practices, including CI/CD pipelines, automated testing, monitoring, and retraining strategies for ML models to ensure continuous improvement and stability.
  • Performance Optimization: Optimize ML models and underlying infrastructure for computational efficiency, speed, and resource utilization.
  • Technical Leadership & Mentorship: Drive technical excellence, promote best coding practices, perform code reviews, and provide mentorship to junior engineers.
  • Cross-Functional Collaboration: Partner closely with data scientists, product managers, and other engineering teams to translate complex business requirements into technical ML solutions and ensure successful delivery.
  • Risk Management & Compliance: Integrate risk assessment and compliance considerations into ML system design and deployment, ensuring adherence to applicable laws, regulations, and internal policies to safeguard the firm's reputation and assets.

Qualifications

  • Experience:
    • 5+ years of hands-on experience in Machine Learning Engineering, MLOps, or AI system development.
    • Minimum of 2 years of direct experience in engineering and deploying Generative AI/LLM solutions in production.
  • Technical Skills:
    • Deep proficiency in Python for production-grade ML development, with expertise in relevant libraries (scikit-learn, pandas, SpaCy, TensorFlow, PyTorch, Hugging Face Transformers).
    • Strong experience with PySpark for large-scale data processing and building robust data pipelines.
    • Proficiency in big data frameworks (Hadoop, Spark, Hive, Hue) and experience with streaming technologies.
    • Extensive experience with MLOps tools and practices (e.g., Docker, Kubernetes, MLflow, Airflow, CI/CD for ML).
    • Proven experience in designing, implementing, and deploying NLP and deep learning models to production.
    • Hands-on experience with Generative AI development, including engineering prompting strategies, RAG implementation, and LLM fine-tuning and integration (e.g., Langchain, LlamaIndex).
    • Familiarity with cloud platforms (AWS, Azure, GCP) and their ML services.
    • Good to have: Experience with graph neural networks, graph databases, or distributed systems for ML.
  • System Design & Architecture: Demonstrated ability to design scalable, fault-tolerant, and performant ML systems.
  • Problem-Solving: Exceptional analytical, interpretive, and problem-solving skills with a focus on engineering challenges and innovative solutions.
  • Communication: Excellent interpersonal, verbal, and written communication skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.
  • Autonomy & Leadership: Proven ability to work independently, drive projects to completion, and provide technical leadership and mentorship

    ------------------------------------------------------

    Job Family Group:

    Technology

    ------------------------------------------------------

    Job Family:

    Digital Software Engineering

    ------------------------------------------------------

    Time Type:

    Full time

    ------------------------------------------------------

    Primary Location:

    Tampa Florida United States

    ------------------------------------------------------

    Primary Location Full Time Salary Range:

    $125,600.00 - $188,400.00


    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

    For complementary skills, please see above and/or contact the recruiter.

    ------------------------------------------------------

    Anticipated Posting Close Date:

    Mar 10, 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.

    Senior Machine Learning Engineer, Vice President

    at Citi

    Back to all Data Science / AI / ML jobs
    Citi logo
    Industry not specified

    Senior Machine Learning Engineer, Vice President

    at Citi

    Mid LevelNo visa sponsorshipData Science/AI/ML

    Posted 9 hours ago

    No clicks

    Compensation
    $125,600 – $188,400 USD

    Currency: $ (USD)

    City
    Tampa
    Country
    United States

    Lead the design, architecture, and deployment of scalable machine learning systems, including advanced NLP and Generative AI (LLM) solutions, across Citi platforms. Own the end-to-end ML lifecycle in production—from deployment to monitoring and retraining—driving performance, reliability, and scalability. Provide technical leadership and mentorship, conducting code reviews and collaborating with data scientists, product managers, and other engineering teams to translate complex business requirements into robust ML solutions while considering risk and regulatory compliance.

    Senior Machine Learning Engineer, Vice President

    Job Req Id:
    26942580
    Location(s):
    Tampa, Florida, United States
    Job Type:
    Hybrid
    Posted:
    Mar. 04, 2026

    Discover your future at Citi

    Working at Citi is far more than just a job. A career with us means joining a team of more than 230,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.

    Job Overview

    Candidate should possess deep hands-on expertise in designing, building, and deploying scalable machine learning systems, including advanced NLP and Generative AI (LLM) solutions. This position demands strong technical leadership, a quick learning ability, a proven track record in delivering high-value, production-grade AI solutions, and the capacity to mentor junior engineers.

    The right candidate will be expected to be a key player in the project evolution & deployment shouldering the following responsibilities:

    Work as a collaborative member of a team spread over multiple locations (India, UK, US) Understand internally published architectural guidelines to design solutions and represent them in architectural reviews. Define & communicate development standards that follow established architectural designs and perform code reviews to ensure quality standards of systems & team. Lead by example in developing exceptional quality code by doing design & code reviews. Design & develop platform functionality that is scalable & configurable as a global platform.

    Key Responsibilities

    • ML System Design & Architecture: Lead the design and architecture of robust, scalable, and high-performance machine learning systems, ensuring seamless integration with existing platforms.
    • Production ML Model Deployment: Own the end-to-end lifecycle of deploying and operationalizing machine learning models in production environments, ensuring efficiency, reliability, and maintainability.
    • Advanced AI/ML Engineering: Develop, optimize, and implement advanced machine learning algorithms and statistical models, focusing on engineering best practices for performance and scalability.
    • Generative AI & NLP System Development: Engineer and integrate cutting-edge Generative AI (LLM) and Natural Language Processing (NLP) solutions. This includes designing efficient prompting strategies, developing LLM-based data augmentation techniques, and implementing Retrieval-Augmented Generation (RAG, including advanced RAG) to enhance model capabilities within production systems.
    • Deep Learning Infrastructure: Design and build systems to effectively apply and deploy deep learning techniques (ANN, LSTM, CNN, BERT, XLNet, Transformers, neural & LLM-based embeddings) for state-of-the-art AI applications at scale.
    • MLOps & Automation: Establish and implement MLOps practices, including CI/CD pipelines, automated testing, monitoring, and retraining strategies for ML models to ensure continuous improvement and stability.
    • Performance Optimization: Optimize ML models and underlying infrastructure for computational efficiency, speed, and resource utilization.
    • Technical Leadership & Mentorship: Drive technical excellence, promote best coding practices, perform code reviews, and provide mentorship to junior engineers.
    • Cross-Functional Collaboration: Partner closely with data scientists, product managers, and other engineering teams to translate complex business requirements into technical ML solutions and ensure successful delivery.
    • Risk Management & Compliance: Integrate risk assessment and compliance considerations into ML system design and deployment, ensuring adherence to applicable laws, regulations, and internal policies to safeguard the firm's reputation and assets.

    Qualifications

    • Experience:
      • 5+ years of hands-on experience in Machine Learning Engineering, MLOps, or AI system development.
      • Minimum of 2 years of direct experience in engineering and deploying Generative AI/LLM solutions in production.
    • Technical Skills:
      • Deep proficiency in Python for production-grade ML development, with expertise in relevant libraries (scikit-learn, pandas, SpaCy, TensorFlow, PyTorch, Hugging Face Transformers).
      • Strong experience with PySpark for large-scale data processing and building robust data pipelines.
      • Proficiency in big data frameworks (Hadoop, Spark, Hive, Hue) and experience with streaming technologies.
      • Extensive experience with MLOps tools and practices (e.g., Docker, Kubernetes, MLflow, Airflow, CI/CD for ML).
      • Proven experience in designing, implementing, and deploying NLP and deep learning models to production.
      • Hands-on experience with Generative AI development, including engineering prompting strategies, RAG implementation, and LLM fine-tuning and integration (e.g., Langchain, LlamaIndex).
      • Familiarity with cloud platforms (AWS, Azure, GCP) and their ML services.
      • Good to have: Experience with graph neural networks, graph databases, or distributed systems for ML.
    • System Design & Architecture: Demonstrated ability to design scalable, fault-tolerant, and performant ML systems.
    • Problem-Solving: Exceptional analytical, interpretive, and problem-solving skills with a focus on engineering challenges and innovative solutions.
    • Communication: Excellent interpersonal, verbal, and written communication skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.
    • Autonomy & Leadership: Proven ability to work independently, drive projects to completion, and provide technical leadership and mentorship

      ------------------------------------------------------

      Job Family Group:

      Technology

      ------------------------------------------------------

      Job Family:

      Digital Software Engineering

      ------------------------------------------------------

      Time Type:

      Full time

      ------------------------------------------------------

      Primary Location:

      Tampa Florida United States

      ------------------------------------------------------

      Primary Location Full Time Salary Range:

      $125,600.00 - $188,400.00


      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

      For complementary skills, please see above and/or contact the recruiter.

      ------------------------------------------------------

      Anticipated Posting Close Date:

      Mar 10, 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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