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About This Role
AI Sales and Digital Marketing Associate
Infinity Energy | Mahwah, NJ (on-site) | $18–20/hour
Build smarter systems. Turn data into action.
Most companies are still figuring out how to use AI. We're already building with it.
Infinity Energy has been installing solar across New York, New Jersey, and Connecticut since 2009, with over 10,000 systems installed. Now, we're improving how the company operates using AI, marketing analytics, and automation to generate leads, optimize campaigns, and streamline business processes.
We're looking for someone with a foundation in digital marketing who enjoys working with data, exploring new technology, and finding smarter ways to get things done. You'll help improve our marketing and sales processes while learning how AI can transform the way a business operates.
What you'll actually do
- Support digital marketing campaigns across Google Ads, Meta Ads, SEO, and lead generation.
- Track and analyze marketing performance using GA4, Google Ads, Excel, and other reporting tools to identify trends and opportunities.
- Conduct keyword research, competitive analysis, and website performance reviews to support SEO and campaign optimization.
- Build and improve marketing automation workflows, lead follow-ups, and customer journeys using CRM and automation platforms.
- Use Claude and ChatGPT to explore AI-powered tools, automate repetitive tasks, and improve sales and marketing workflows.
- Work directly with company leadership to test ideas, solve problems, and turn insights into practical solutions.
Who we're looking for
We're looking for someone who has hands-on experience through internships, projects, or early-career roles and is ready to take their skills further.
You might be a great fit if you:
- Have experience with digital marketing, paid media, SEO, social media, marketing analytics, or lead generation.
- Have worked with tools such as Google Ads, Meta Ads, GA4, Excel, Semrush, CRM platforms, or marketing automation software.
- Understand marketing metrics such as clicks, conversions, ad spend, cost per lead, and campaign performance.
- Are comfortable organizing data, researching competitors, and using insights to recommend improvements.
- Are curious about AI and excited to learn how tools like Claude and ChatGPT can improve workflows and business operations.
- Are organized, detail-oriented, proactive, and comfortable managing multiple projects.
Recent graduates and early-career candidates are encouraged to apply. We're interested in practical experience, initiative, and the ability to learn—not just a list of credentials.
Why this role is worth taking
You'll join an established company at a time when we're actively investing in AI and automation. You'll gain hands-on experience across digital marketing, sales, analytics, and emerging technology while working directly with company leadership.
You'll have the opportunity to improve real campaigns, build smarter workflows, and explore AI-powered solutions that make a measurable difference. As the company grows, so can your responsibilities and opportunities to take ownership of new initiatives.
The details
- Title: AI Sales and Digital Marketing Associate
- Location: On-site at our headquarters, 575 Corporate Dr., Suite 2200, Mahwah, NJ 07430
- Pay: $18–20/hour, depending on experience
- Schedule: Full-time
- Reports to: Company ownership
About Infinity Energy
Infinity Energy (Infinity Solar Systems LLC) was founded in 2009 by two childhood friends, one from roofing and one from electrical. We're one of the few contractors in the country that's both a full solar installer and a GAF Master Elite roofing contractor. Everything is in-house: consultation, engineering, permitting, installation, electrical, and roofing.
We're rated Elite+ on EnergySage, were named EnergySage Installer of the Year, and hold an A+ rating with the Better Business Bureau.
How to apply
Send your resume to [email protected] with a short note telling us about a marketing campaign, project, report, or workflow you've worked on or improved.
No cover letter template. Just tell us what you've made.
Pay: $18.00 - $20.00 per hour
Experience:
- Digital marketing: 1 year (Required)
- AI : 1 year (Required)
Ability to Commute:
- Mahwah, NJ 07430 (Required)
Work Location: In person
Salary Context
This $37K-$41K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 2094 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 10,827 AI roles we're tracking, AI/ML Engineer positions make up 77% of the market. At Infinity Energy, 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 $212,160 based on 13,809 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $112,320. This role's midpoint ($39K) sits 81% below the category median. Disclosed range: $37K to $41K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,111. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,300; VP: $236,450.
Infinity Energy AI Hiring
Infinity Energy has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Mahwah, NJ, US. Compensation range: $41K - $41K.
Location Context
Across all AI roles, 6% (665 positions) offer remote work, while 10,097 require on-site attendance. Top AI hiring metros: New York (3,262 roles, $221,000 median); San Francisco (2,767 roles, $260,600 median); Los Angeles (1,585 roles, $210,000 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 10,827 open positions tracked in our dataset. By seniority: 122 entry-level, 5,256 mid-level, 3,922 senior, and 1,527 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (665 positions). The remaining 10,097 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,111. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 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 10,827 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,288), AI Software Engineer (548), AI Product Manager (471). 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 (122) are outnumbered by mid-level (5,256) and senior (3,922) 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 1,527 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (665 positions), with 10,097 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 $213,480. Top-quartile roles start at $264,111, and the 90th percentile reaches $318,400. 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 Safety roles lead at $266,050 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 (2,093 postings), Aws (1,100 postings), Azure (910 postings), Rag (863 postings), Gcp (680 postings), Pytorch (549 postings), Claude (532 postings), Kubernetes (511 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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