AI/ML Engineer, Assistant Vice President

Citi • Tampa, FL

1d

About The Position

We are seeking a talented and motivated Mid-level AI/ML Engineer to join our Artificial Intelligence and Machine Learning team. This role focuses on the implementation, optimization, and deployment of machine learning systems, including NLP and Generative AI solutions. The ideal candidate will possess hands-on experience in building and deploying ML models, a solid understanding of ML principles, and the ability to work collaboratively within a distributed team. This position offers an excellent opportunity to grow technically, contribute to high-value AI solutions, and learn from experienced engineers. The right candidate will be expected to be a collaborative member contributing to project evolution & deployment, shouldering the following responsibilities: Work as a collaborative member of a team spread over multiple locations (India, UK, US). Adhere to internally published architectural guidelines and participate in architectural discussions and reviews. Contribute to defining and communicating development standards that follow established architectural designs and participate in code reviews to ensure quality standards. Develop high-quality code and actively participate in design & code reviews. Assist in designing and developing scalable & configurable platform functionality for global applications.

Requirements

• Experience: 3 +years of hands-on experience in Machine Learning Engineering, MLOps, or AI system development. Some experience or familiarity with Generative AI/LLM concepts and their application.
• Technical Skills: Proficiency in Python for ML development, with experience in relevant libraries (scikit-learn, pandas, SpaCy, TensorFlow, PyTorch, Hugging Face Transformers).
• Experience with PySpark for large-scale data processing and building data pipelines.
• Familiarity with big data frameworks (Hadoop, Spark, Hive, Hue) and exposure to streaming technologies.
• Experience with MLOps tools and practices (e.g., Docker, Kubernetes, MLflow, Airflow, CI/CD for ML).
• Experience in implementing and deploying NLP and deep learning models.
• Familiarity with Generative AI development concepts, including prompting strategies and RAG implementation.
• Familiarity with cloud platforms (AWS, Azure, GCP) and their ML services.
• System Design & Architecture: Understanding of scalable and performant ML system design principles.
• Problem-Solving: Strong analytical, interpretive, and problem-solving skills with a focus on engineering challenges.
• Communication: Good interpersonal, verbal, and written communication skills, with the ability to articulate technical concepts.
• Autonomy & Growth: Ability to work independently on assigned tasks, contribute to project completion, and a strong willingness to learn and grow from senior team members.

Nice To Haves

• Exposure to graph neural networks, graph databases, or distributed systems for ML.
• Experience with frameworks like Langchain or LlamaIndex is a plus.

Responsibilities

• ML System Design & Architecture: Contribute to the design and architecture of scalable machine learning systems, ensuring integration with existing platforms.
• Production ML Model Deployment: Support the end-to-end lifecycle of deploying and operationalizing machine learning models in production environments, focusing on efficiency, reliability, and maintainability.
• AI/ML Engineering: Develop, optimize, and implement machine learning algorithms and statistical models, focusing on engineering best practices for performance and scalability.
• Generative AI & NLP System Development: Implement and integrate Generative AI (LLM) and Natural Language Processing (NLP) solutions. This includes assisting in designing prompting strategies, developing LLM-based data augmentation techniques, and implementing Retrieval-Augmented Generation (RAG, including advanced RAG) to enhance model capabilities within production systems.
• MLOps & Automation: Participate in the implementation and adherence to MLOps practices, including CI/CD pipelines, automated testing, monitoring, and retraining strategies for ML models.
• Performance Optimization: Contribute to the optimization of ML models and underlying infrastructure for computational efficiency, speed, and resource utilization.
• Technical Contribution & Learning: Actively participate in technical discussions, adhere to best coding practices, and engage in code reviews to continuously improve code quality and personal skills.
• Cross-Functional Collaboration: Partner with data scientists, product managers, and other engineering teams to translate business requirements into technical ML solutions and ensure successful delivery.
• Risk Management & Compliance: Adhere to risk assessment and compliance guidelines in ML system design and deployment, ensuring adherence to applicable laws, regulations, and internal policies.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed