Interested in this AI/ML Engineer role at PenFed Credit Union?
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Job Overview
PenFed is hiring a (Hybrid) Senior AI Program Analyst at our Tysons, Virginia or San Antonio, Texas location. The Senior AI Program Analyst supports the scaling of the enterprise Responsible AI program by reviewing governance frameworks, policies, procedures, and the AI portfolio and completing analysis to support repeatable, inspectable, and defensible operational execution.
This role focuses on policy support, testing and monitoring assurance, AI intake and inventory operations, and governance enablement. The Analyst does not design or build AI models, nor do they independently approve risk outcomes. Instead, they support analysis of the AI portfolio as it pertains to Responsible AI policies and standards.
Responsibilities
Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This is not intended to be an all\-inclusive list of job duties and the position will perform other duties as assigned.
- Responsible AI Analysis \& Program Enablement
+ Support analysis of AI outcomes by helping determine evaluation scope, datasets, and assessment approaches based on a given AI use case.
+ Prepare summaries, data, and other materials related to the Responsible AI program for executive briefings, audits, and risk reviews.
+ Review AI testing and monitoring data for outcomes against established Responsible AI policies and standards.
+ Complete thorough analysis of use cases to identify gaps, inconsistencies, or missing evidence and escalate findings to Responsible AI leadership.
- Policy \& Procedure Support
+ Draft and maintain Responsible AI policies, procedures, and related documentation.
+ Coordinate reviews and feedback across Legal, Compliance, IT, Risk, and other stakeholders.
+ Prepare summaries of procedural changes and clarifications for stakeholder communication.
- Regulatory \& Standards Research
+ Monitor AI governance standards and regulatory developments as they relate to financial services and Responsible AI.
+ Provide targeted research to support policy updates and leadership briefings.
Qualifications
Equivalent combination of education and experience is considered.
- Bachelor's degree or equivalent experience in governance, risk management, public policy, information systems, data, or related fields.
- Minimum 5 years of experience in AI, governance, risk, compliance, audit, or policy.
- Proficiency in data analysis and statistical methods required.
- Strong understanding of AI/ML principles, bias detection, model monitoring, and explainability.
- Familiarity with regulatory compliance and ethical AI best practices preferred.
- Exceptional written communication skills and strong oral communication skills.
- Strong leadership and stakeholder engagement skills.
- Strong analytical, interpersonal, and decision\-making skills.
- Experience in financial services or other regulated industries preferred.
- Experience with AI observability platforms and governance tools preferred.
- Experience in using A.I. tools preferred.
Supervisory Responsibility
This position will not supervise employees.
Licenses and Certifications
There are no additional certifications required.
Work Environment
While performing the duties of this job, the employee is regularly exposed to an indoor office setting with moderate noise.
\*Most roles require working in an office setting with moderate noise and the ability to lift 25 pounds.\*
Travel
No travel required.
\#LI\-Hybrid
Benefits
At PenFed, we offer a robust benefits package designed to support you both personally and professionally. You'll have access to comprehensive health, dental, and vision plans; paid time off; and family\-friendly benefits like paid parental leave, care support, and fitness center access. Financial wellness is encouraged through features like a 401(k) match, employee loan discounts, and fully paid life and disability coverage. We also support growth via education assistance, community involvement, and volunteer opportunities.
Our Purpose
Helping members achieve their dreams since 1935\.
Pentagon Federal Credit Union (PenFed) is one of America's largest federal credit unions, serving 2\.8 million members worldwide with $29 billion in assets. PenFed offers market\-leading certificates, checking and savings, credit cards, personal loans, mortgages, auto loans, and a wide range of other financial services, always with members' interests in mind. PenFed is federally insured by the NCUA and is an Equal Housing Lender.
Berkshire Hathaway HomeServices PenFed Realty, LLC is a full\-service real estate company ready to assist our clients with buying, selling and renting a home. The company is a wholly owned subsidiary of PenFed Credit Union and is the largest independently\-owned brokerage in the Berkshire Hathaway HomeServices network, placing us in the top 1% of all real estate brokerages in the country.
With almost 60 offices and nearly 2,000 world\-class sales professionals, we offer complete service coverage in Virginia, Maryland, the District of Columbia, Delaware, Pennsylvania, West Virginia, Florida, Tennessee, Kansas and Texas. In addition, we also offer specialized client services which include management of vacation properties and long\-term rentals, corporate relocation services and national referral network.
Equal Employment Opportunity
PenFed management will maintain and observe personnel policies which will not discriminate or permit harassment or retaliation against a person because of race, color, creed, age, sex, gender, gender identity, gender expression, religion, national origin, ancestry, marital status, military or veteran status or obligation, the presence of a physical and/or mental disability or medical condition, genetic information, sexual orientation, and all statuses protected by applicable state or local law in all recruiting, hiring, training, compensation, overtime, position classifications, work assignments, facilities, promotions, transfers, employee treatment, and in all other terms and conditions of employment. PenFed will also prohibit retaliation against individuals for raising a complaint of discrimination or harassment or participating in an investigation of same.
PenFed will also reasonably accommodate qualified individuals with a disability so that they can apply for a job or perform the essential functions of a job unless doing so causes a direct threat to these individuals or others in the workplace and the threat cannot be eliminated by reasonable accommodation or if the accommodation creates an undue hardship to PenFed. Contact human resources (HR) with any questions or requests for accommodation at 402\-639\-8568\.
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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At PenFed Credit Union, 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 in Demand for This Role
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 $181,170 based on 12,692 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
PenFed Credit Union AI Hiring
PenFed Credit Union has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span San Antonio, TX, US, McLean, VA, US.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 median).
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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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