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About This Role
Your Role...:
By exhibiting exceptional teamwork, boundless curiosity, and the utmost care, the Retail Store Sales Associate will assist their team to fulfil Blick’s commitment to our customers, the Arts, and our local communities. The Retail Store Sales Associate will do this by maintaining outstanding customer service, generating revenue though helpful product knowledge, housekeeping, merchandising, signing, pricing, POS operations, and loss prevention in adherence to all company policies and procedures. Responsibilities include,* Consistently delivers superior customer service by combining sales, product knowledge, and other skills training to meet or exceed customer expectations.
- Completes and utilizes the following programs: Blick Onboarding Training, Blick Sales Training, Preferred Customer Program, Special Orders, and Custom Services
- Training from NDS.
- Provide customer service at the Custom Services desk including making appointments for customers, consulting with customers on their Custom Services project, taking Custom Services orders, and delivering completed Custom Services orders in store.
- Displays an energetic and positive attitude with all customer interactions.
- Assist in the coordination of merchandise set\-ups, has knowledge of visual standards and techniques, and has the ability to implement and maintain the store as set forth by store management.
- Follows directions and prioritizes tasks to meet deadlines assigned with minimal supervision.
- Understands and acts on the procedures required for reporting low stock levels, inventory discrepancies, and customer product requests to management as needed.
General Requirements:* Ability to work both independently and in a team environment.
- Excellent Communication Skills.
- Working knowledge of a variety of traditional fine art mediums preferred, including but not limited to: paints, markers, pencils, print making materials, clay, papers etc.
Scheduling Requirements:* Availability to work flexible schedules including day/evening shifts, weekends and holidays as required by the needs of the business.
- Regular attendance in accordance with the retail attendance policy.
- Associates in this role are scheduled an average of 15 \- 25 hours per week based on availability and the needs of the business
Competencies:* Elevates Service Standards
- Leadership
- Champions Core Values
- People
- Operations
Supervisory Responsibility:* This position has no supervisory responsibilities.
Physical Demands:* Must be able to lift and carry 50 pounds while using the appropriate lifting techniques and following all safety rules.
- Prolonged walking, standing, and climbing ladders.
Travel:* Minimal travel in the local area may be required.
Qualifications:* High School Graduate or equivalent.
Other Duties:
This job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the associate for this job. Duties, responsibilities, and activities may change at any time with or without notice. Pay Rate:
The pay range below is provided in compliance with state/city specific laws. This pay range applies to this location. Pay ranges may be different in other locations.* $16\.25 \- $ 16\.50 per hour \+ Sales Incentives
Benefits Include:* 401K \& Profit Sharing Plan
- Incentive Bonus Plans
- Paid Time Off
- Employee Discount
Who we are...:
Founded in 1911, Blick Art Materials is in its third generation of family ownership, and is the largest and oldest provider of art supplies in the United States.
Our Mission...:
At Blick Art Materials, our family owners and dedicated staff support the Visual Art Community by providing the widest selection of art supplies at the lowest prices. With extraordinary service and integrity, we strive to provide artists, educators, students, and our employees with the tools, assistance, and training they need to grow, innovate, and reach their creative potential.
Salary Context
This $33K-$33K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $100K across 15465 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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At BLICK Art Materials, 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 $166,983 based on 13,781 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $76,880. This role's midpoint ($33K) sits 80% below the category median. Disclosed range: $33K to $33K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
BLICK Art Materials AI Hiring
BLICK Art Materials has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Paramus, NJ, US, New York, NY, US. Compensation range: $33K - $82K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 $122,200. 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 (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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