ML Engineer, AVP
MUFG•Jersey City, NJ
•Hybrid
About The Position
The MLOps Engineer – Analyst (Gen AI Focus) will support the deployment, monitoring, and optimization of Generative AI solutions across the enterprise AI ecosystem, including LLM-based applications, copilots, and AI agents. This entry-level role is designed for recent graduates looking to work at the intersection of Generative AI, cloud platforms, and enterprise-scale operations, with a focus on responsible AI, governance, and production readiness in a regulated banking environment.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, Data Science, or related field, or equivalent work experience.
- Foundational knowledge of Python, APIs and REST services, Machine Learning basics, and Basic understanding of Large Language Models (LLMs).
- Academic projects or internships involving AI/ML or Gen AI.
- Technical Skills: Python / scripting.
- LLM fundamentals (prompting, inference, evaluation).
- API integration and data handling.
- Basic cloud & DevOps concepts.
- Analytical thinking and curiosity (critical for Gen AI experimentation).
- Attention to detail (important for model validation and risk control).
- Strong communication and collaboration skills.
- Willingness to learn quickly in a fast-evolving AI landscape.
Nice To Haves
- Exposure to: Generative AI (e.g., ChatGPT, Azure OpenAI, LLM APIs); Prompt engineering concepts; Vector databases / embeddings (basic familiarity); Cloud platforms (AWS, Azure).
Responsibilities
- Assist in deploying and managing LLM-powered applications (chatbots, copilots, AI agents).
- Support integration of Gen AI models (e.g., prompt workflows, APIs, retrieval layers) into enterprise systems.
- Help onboard business use cases onto enterprise platforms.
- Support creation, testing, and refinement of prompts and prompt templates.
- Assist in evaluating response quality, consistency, and hallucination risks.
- Work with senior engineers to improve accuracy, grounding, and reliability of AI outputs.
- Assist in building and testing RAG pipelines (connecting Gen AI models with enterprise data).
- Support data ingestion, indexing, and validation workflows.
- Help ensure responses are grounded in approved enterprise data sources.
- Monitor Gen AI systems for: Output quality, Latency and performance, Safety and compliance issues.
- Support creation of evaluation metrics and test datasets for Gen AI use cases.
- Assist in identifying and escalating issues such as hallucination, bias, or drift.
- Contribute to automation of LLM lifecycle workflows (deployment, testing, monitoring).
- Assist in building reusable workflows using: CI/CD pipelines, API integrations, Low-code/no-code automation tools.
- Follow enterprise AI governance standards for: Model usage, Prompt logging and monitoring, Data privacy and compliance.
- Assist in documenting Gen AI use cases for audit and regulatory purposes.
- Support enforcement of Responsible AI principles (fairness, explainability, security).
- Partner with: AI engineers, Data scientists, Business teams.
- Participate in use case onboarding, PoCs, and production scaling efforts.
- Continuously build knowledge in Gen AI tools, frameworks, and best practices.
Benefits
- comprehensive health and wellness benefits
- retirement plans
- educational assistance and training programs
- income replacement for qualified employees with disabilities
- paid maternity and parental bonding leave
- paid vacation, sick days, and holidays
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
