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About This Role
DESCRIPTIVE SUMMARY
The Vice President of Retail Banking reports to the SVP of Operations. As a member of the Credit Union’s retail management team, this position plays a key role in driving organizational goals and our mission.
Directs all aspects of operations for multiple branches and call center to ensure effective and efficient operations, quality of member service, and compliance with existing regulations and policies for each location.
Participates in the strategic planning and management of the retail division. This position will oversee the administration of the Credit Union Service Organization NDIP (CUSO), including IC Insurance, Investments, and Retirement programs.
ESSENTIAL JOB FUNCTIONS
- Responsible for the hiring and personnel development of all Retail Banking Managers.
- Mentor and develop branch leadership, fostering an environment of continuous learning and professional growth ensuring that all employees are properly trained, mentored and supervised in a manner that is consistent with the strategic/tactical goals and objectives of the credit union.
- Establish objectives and performance goals for the Retail Management Team that contributes to achieving the Credit Union’s overall goals.
- Demonstrate leadership in words and actions daily, act as a role model for success and engagement.
- Create a positive work environment conducive to trust and transparency, ensuring branch cooperation, respect and teamwork with other branches, departments and members.
- Communicate organizational goals, changes, and updates to branch teams, ensuring alignment and clarity.
- Develop and analyze branch performance metrics, member feedback, and market trends to identify opportunities for growth and to measure the effectiveness of sales and service activities. Modify processes as needed.
- Responsible for overall sales performance of branches. Plan, direct, and manage the business development, service, and sales activities in accordance with the organization’s strategic and corporate goals.
- Develop sales and incentive programs that contribute to increased member profitability and branch operation efficiencies.
- Partner with senior leadership to develop and execute retail branch strategies that align with organizational goals and priorities.
- Lead and participate in special projects, including branch expansions, relocations, and process enhancements.
- Keep abreast of changes in the industry and changing trends to react in a way that maintains competitiveness.
- Responsible for the development and enforcement of various credit union policies and procedures. Ensure that all staff members have appropriate knowledge of related regulations and guidelines.
- May serve on Ad Hoc Committees including ALM, Supervisory, and Compliance.
- Oversee all branch operations, retail delivery channels, and member service functions ensuring branch operational and compliance tasks are achieved.
- Support marketing campaigns, product rollouts, community engagement efforts, and financial education initiatives.
- Foster a culture of exceptional member service across all branches by promoting best practices and adopting a service-first mindset.
- Manage and support the IC Retirement and Investments CUSO’s (NDIP) including maintaining strong, mutually beneficial relationships with the sponsored broker/dealer. Provide regular reports relating to the progress of the CUSO’s business plans.
- Manage vendor relationships and evaluate technology solutions that enhance retail division. Conduct vendor due diligence reviews within the Retail area.
- Develop and manage the retail division’s annual budget, including staffing, facilities, and operational expenses. Analyze financial performance and ensure branches operate within budget while meeting growth and efficiency targets.
OTHER DUTIES
Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.
JOB COMPETENCIES
- Budget Development & Control: The degree to which the individual projects, develops, and meets budgets, in accordance with company financial guidelines and controls.
- Management Effectiveness: The overall ability to supervise and direct people and/or resources to meet department goals. The level at which one is able to motivate people, plan and prioritize unit operations, respond to changing conditions, and manage costs effectively.
- Membership & Deposit Growth: The level of membership and deposit growth achieved as compared against a pre-determined goal.
- Organizational Relations: The degree to which the employee collaboratively works with other internal departments, agencies, and/or outside organizations. The level of response to customer requests, both internally and externally. Anticipation and control of obstacles.
- Results Driven: Defines appropriate goals, works toward achieving goals, articulates vision and steps for achievement.
- Public Relations: The level of focus and professional service provided to customers and outside contacts. The productive relationship with community groups, outside representatives, and businesses within the competitive environment. The ability to diffuse problems and maintain a positive image of the organization.
- Sales Leadership: Ability to develop, manage, and execute organizational sales plans and promotions, to meet overall company sales goals through effective leadership of retail management team.
- Strategic Planning: The degree to which the incumbent gathers and interprets data, appropriately applies knowledge to the planning process, and generates strategic plans that contribute to the short- and long-term goals and objectives of the organization. Effectively conveys the vision, strategy, goals, and culture of the organization. Takes into account strengths, weaknesses, opportunities, threats, and any other factor that might possibly affect company objectives.
EDUCATION/EXPERIENCE REQUIREMENTS *(Education, Work Experience, Industry Knowledge)*
- A bachelor’s degree or equivalent with knowledge of marketing, sales and business development, banking operations and general management skills is required.
- Seven to ten years of related retail experience, five of which should be in the managerial capacity of a credit union or other financial institution.
- The individual must have a good working knowledge of channel management and development and be aware of emerging trends in the delivery of financial products and services.
- Must have experience in managing and motivating sales teams to meet their objectives and performance goals.
- The individual must possess self-initiative, excellent communication skills, a strong commitment to member service, and the ability to work collaboratively in a team environment.
- Excellent verbal, research, and written communications skills.
- Must possess strong Excel, Word, PowerPoint, and other database application skills.
PHYSICAL DEMANDS
Physical requirements include, but are not limited to, high-pressure office environment; ability to multitask; ability to work unusual hours including early morning, late evenings and weekends as needed.
REQUIRED COMPLIANCE TRAINING
Satisfactorily completes all required compliance training and complies with all regulations which apply within the scope of the position, including but not limited to the Bank Secrecy Act (BSA) and all regulations that fall within the BSA.
*The above is intended to describe the general content of and requirements for the performance of this job. It is not to be construed as an exhaustive statement of duties, responsibilities, or physical requirements. Nothing in this job description restricts management’s right to assign or reassign duties and responsibilities to this job at any time.* *Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.*
Monday - Friday, 8:00am-5:00pm
Salary Context
This $104K-$135K range is below the median for AI/ML Engineer roles in our dataset (median: $170K across 217 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 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At IC 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 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 $154,000 based on 8,743 positions with disclosed compensation. This role's midpoint ($119K) sits 22% below the category median. Disclosed range: $104K to $135K.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
IC Credit Union AI Hiring
IC Credit Union has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Fitchburg, MA, US. Compensation range: $135K - $135K.
Location Context
Across all AI roles, 7% (2,732 positions) offer remote work, while 34,484 require on-site attendance. Top AI hiring metros: New York (1,633 roles, $204,100 median); Los Angeles (1,356 roles, $179,440 median); San Francisco (1,230 roles, $240,000 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 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 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 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). 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 (3,672) are outnumbered by mid-level (23,272) and senior (7,048) 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 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 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 $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. 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 $293,500 median, while Prompt Engineer roles sit at $145,600. 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: Rag (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 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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