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About This Role
### General Information
Location
New York, New York
Working Schedule
Part\-Time
Work Arrangement
Hybrid
Relocation Assistance Available
No
Grade
DEV
Posted Date
30\-Jul\-2026
Job ID
19381
### Description and Requirements
The Opportunity
Are you interested in artificial intelligence, user experience design, and process improvement? Do you enjoy solving complex problems, understanding user needs, and finding innovative ways to make work more efficient and effective?
MetLife is seeking an analytical, collaborative, and user\-focused student to join our Internal Audit team as a part\-time intern. Internal Audit plays a critical role in evaluating business, financial, and technology processes to help ensure effective risk management, regulatory compliance, and operational excellence. This internship offers hands\-on exposure to user experience design, workflow optimization, artificial intelligence, and business operations while supporting Global Professional Practices \& Operations initiatives across Internal Audit. Working alongside experienced audit and technology professionals, you will help design intuitive user experiences, explore AI\-enabled solutions, and improve workflows that support audit planning, reporting, knowledge management, and operational effectiveness.
This part\-time internship runs from October 2026 through May 2027\. Interns will work approximately 20 hours per week and are expected to be in their designated office three days per week based on a schedule agreed upon with their manager.
Key Responsibilities
- Conduct user discovery activities to identify workflow challenges, user needs, and opportunities for process improvement.
- Create user stories, process maps, journey maps, wireframes, and prototypes to enhance user experiences and simplify workflows.
- Support AI initiatives by developing prompt libraries, documenting requirements, gathering feedback, and evaluating use cases.
- Collaborate with Internal Audit and Technology stakeholders to gather requirements, test solutions, and refine deliverables.
- Research emerging AI, digital productivity, and user experience trends to drive efficiency and innovation.
- Develop presentations, training materials, and recommendations while managing project work, communicating progress, and building strong stakeholder relationships.
Required Qualifications
- Current Sophomore, Junior, or Senior enrolled in a Bachelor's degree program at an accredited university pursuing a degree in UX Design, Human\-Computer Interaction, Information Systems, Business Analytics, Data Science, Computer Science, Industrial Engineering, or a related field.
- Minimum cumulative GPA of 3\.0\.
- Experience using generative AI tools and prompt engineering to support research, analysis, content creation, and workflow optimization.
- Coursework or project experience in user\-centered design, process improvement, digital transformation, automation, or related business solutions.
- Strong analytical, communication, organizational, and problem\-solving skills, with proficiency in Microsoft Excel, Word, Outlook, and PowerPoint.
Preferred Qualifications
- Currently enrolled in a Master’s degree program at an accredited college or university.
- Familiarity with tools and platforms such as Microsoft 365 Copilot, Power Automate, SharePoint, Teams, Visio, or other workflow and collaboration technologies.
- Experience designing or implementing AI\-enabled solutions, including prompt libraries, AI assistants, workflow automations, knowledge management solutions, or low\-code/no\-code applications.
- Experience in creating and documenting UX and process\-design artifacts such as process maps, journey maps, wireframes, prototypes, or workflow diagrams.
- Demonstrated interest in artificial intelligence, user experience design, workflow optimization, digital transformation, or data\-driven decision\-making.
Location Expectation: This is a hybrid role requiring a minimum of 3 days per week in office.
*The expected salary range for this position is$25 \- $30. This role may also be eligible for annual short\-term incentive compensation and stock\-based long\-term incentives. All incentives and benefits are subject to the applicable plan terms.*
About MetLife
Recognized on Fortune magazine's list of the "World's Most Admired Companies", Fortune World’s 25 Best Workplaces™, as well as the Fortune 100 Best Companies to Work For®, MetLife, through its subsidiaries and affiliates, is one of the world’s leading financial services companies; providing insurance, annuities, employee benefits and asset management to individual and institutional customers. With operations in more than 40 markets, we hold leading positions in the United States, Latin America, Asia, Europe, and the Middle East.
As part of our New Frontier strategy, MetLife is building an AI\-enabled, people\-centered future. We’re looking for people who bring curiosity, adaptability, and a growth mindset as we use AI to enhance how we serve customers, support communities, and evolve the way work gets done. At MetLife, AI is a responsible partner that supports human judgment, creativity, and continuous improvement while helping us build trust, inclusion, and long\-term value.
Our purpose is simple \- to help our colleagues, customers, communities, and the world at large create a more confident future. United by purpose and guided by our core values \- Win Together, Do the Right Thing, Deliver Impact Over Activity, and Think Ahead \- we’re inspired to transform the next century in financial services. At MetLife, it’s \#AllTogetherPossible. Join us!
*MetLife is an Equal Opportunity Employer. All employment decisions are made without regards to race, color, national origin, religion, creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity or expression, age, disability, marital or domestic/civil partnership status, genetic information, citizenship status (although applicants and employees must be legally authorized to work in the United States), uniformed service member or veteran status, or any other characteristic protected by applicable federal, state, or local law (“protected characteristics”).* *If you need an accommodation due to a disability, please email us at [email protected]. This information will be held in confidence and used only to determine an appropriate accommodation for the application process.*
*MetLife maintains a drug\-free workplace.*
*This posting is for a current vacancy and is anticipated to remain open for at least 90 days from the listed posting date.*
Salary Context
This $52K-$62K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At MetLife, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $110,000. This role's midpoint ($57K) sits 73% below the category median. Disclosed range: $52K to $62K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
MetLife AI Hiring
MetLife has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Cary, NC, US, New York, NY, US. Compensation range: $62K - $180K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 tracked positions.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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