ML Engineer, Analyst

Discover your opportunity with Mitsubishi UFJ Financial Group (MUFG), one of the world’s leading financial groups. Across the globe, we’re 150,000 colleagues, striving to make a difference for every client, organization, and community we serve. We stand for our values, building long-term relationships, serving society, and fostering shared and sustainable growth for a better world.

With a vision to be the world’s most trusted financial group, it’s part of our culture to put people first, listen to new and diverse ideas and collaborate toward greater innovation, speed and agility. This means investing in talent, technologies, and tools that empower you to own your career.

Join MUFG, where being inspired is expected and making a meaningful impact is rewarded.

The selected colleague will work at an MUFG office or client sites four days per week and work remotely one day. A member of our recruitment team will provide more details.

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.

1) Gen AI Application Deployment & Support

• 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.

• Bachelor’s degree in: • Advanced degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, Data Science, or related field, or equivalent work experience equally preferable.
• Foundational knowledge of: Python, APIs and REST services, Machine Learning basics, and Basic understanding of Large Language Models (LLMs).

• Exposure to: Generative AI (e.g., ChatGPT, Azure OpenAI, LLM APIs); Prompt engineering concepts; Vector databases / embeddings (basic familiarity); Cloud platforms (AWS, Azure).
• 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.

•Bachelor's degree in Computer Science or a closely-related discipline, or an equivalent combination of formal education and experience

The typical base pay range for this role is as follows:

• New York / New Jersey: $108k–$130k

Our hybrid work schedule is four days on-site and work remotely one day per week.

[MUFG Benefits Summary](

We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws (including (i) the San Francisco Fair Chance Ordinance, (ii) the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, (iii) the Los Angeles County Fair Chance Ordinance, and (iv) the California Fair Chance Act) to the extent that (a) an applicant is not subject to a statutory disqualification pursuant to Section 3(a)(39) of the Securities and Exchange Act of 1934 or Section 8a(2) or 8a(3) of the Commodity Exchange Act, and (b) they do not conflict with the background screening requirements of the Financial Industry Regulatory Authority (FINRA) and the National Futures Association (NFA). The major responsibilities listed above are the material job duties of this role for which the Company reasonably believes that criminal history may have a direct, adverse and negative relationship potentially resulting in the withdrawal of conditional offer of employment, if any.

The above statements are intended to describe the general nature and level of work being performed. They are not intended to be construed as an exhaustive list of all responsibilities duties and skills required of personnel so classified.

We are proud to be an Equal Opportunity Employer and committed to leveraging the diverse backgrounds, perspectives and experience of our workforce to create opportunities for our colleagues and our business. We do not discriminate on the basis of race, color, national origin, religion, gender expression, gender identity, sex, age, ancestry, marital status, protected veteran and military status, disability, medical condition, sexual orientation, genetic information, or any other status of an individual or that individual’s associates or relatives that is protected under applicable federal, state, or local law.