Interested in this AI/ML Engineer role at Elysium Energy Solutions?
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AI Creative Marketing & Social Media SpecialistTurn Your Creativity Into a Career!
Company: U.S. Solar Enterprise Inc. Location: Holtsville, NY – Long Island Job Type: Full-Time | Entry-Level Friendly Experience: College experience, creative projects, or self-taught skills welcome Compensation: Based on experience and skills, with opportunities for growth
Love AI, Social Media, Video Editing, or Creating Cool Content? We Want to Meet You!
Are you the person who is always experimenting with ChatGPT, creating videos, designing graphics, editing photos, or discovering the latest AI tools?
Do you enjoy making TikToks, Instagram Reels, YouTube videos, or creative digital content?
Maybe you're currently in college, recently graduated, or taught yourself how to use AI and editing programs just because you enjoy them.
If this sounds like you, this could be the perfect opportunity!
U.S. Solar Enterprise is looking for a creative, motivated, and tech-savvy individual to join our growing team and help us bring our marketing to the next level.
You do NOT need years of professional marketing experience.
We're more interested in your creativity, personality, willingness to learn, and excitement about the future of artificial intelligence.
Who We Are
U.S. Solar Enterprise is a Long Island-based company specializing in:
- Residential and commercial solar energy
- Roofing installations and repairs
- Whole-home battery backup systems
- Electrical services and home energy solutions
We're looking to bring fresh ideas, exciting content, and innovative AI technology into our business.
We want someone who can help us stand out online, reach new customers, and have fun creating content along the way!
What You'll Be Doing Get Creative With Videos & Social Media
- Create fun, engaging Instagram Reels, TikToks, Facebook posts, and YouTube Shorts.
- Turn real job-site photos and videos into awesome marketing content.
- Edit before-and-after transformations of roofing and solar projects.
- Help create eye-catching ads, graphics, and promotional videos.
- Brainstorm creative campaigns with our team.
- Help manage and grow our social media pages.
Explore Artificial Intelligence
This is where things get exciting!
You'll have the opportunity to experiment with AI programs and discover how they can help our business grow.
Some of the tools you might work with include:
- ChatGPT and other AI assistants
- Canva and Adobe creative tools
- CapCut and AI video editing programs
- Runway and other AI video platforms
- AI image generation and graphic design tools
- AI-powered marketing and automation platforms
Have a cool idea for using AI? We want to hear it!
We're looking for someone who enjoys exploring new technology and isn't afraid to try something different.
Learn Digital Advertising & Marketing
Don't worry if you're not an expert in advertising. You'll have the opportunity to learn and develop skills in:
- Facebook and Instagram advertising (Meta Ads)
- Google Ads and YouTube advertising
- Search Engine Optimization (SEO)
- Website content and design
- Digital lead generation
- AI-assisted marketing campaigns
- Social media growth strategies
- Marketing analytics and performance tracking
You'll get hands-on experience learning how businesses use digital marketing to attract customers and grow.
Bring Your Ideas to Life
We don't want someone who just sits behind a desk following instructions all day.
We want someone who brings fresh ideas to the table!
You might be creating an AI-generated promotional video one day, designing a social media campaign the next, or visiting one of our projects to capture footage for an exciting before-and-after transformation.
You'll have the freedom to be creative, experiment with new ideas, and help shape our company's digital presence.
Who Would Be a Great Fit?
You might be perfect for this position if:
- You're currently studying or have studied marketing, communications, graphic design, digital media, computer science, or a related subject.
- You enjoy using AI tools like ChatGPT or AI image and video generators.
- You've edited videos for yourself, friends, school projects, or social media.
- You have experience with Canva, CapCut, Photoshop, Premiere Pro, or similar programs.
- You enjoy social media and understand what makes content interesting.
- You're creative, organized, and excited to learn.
- You enjoy technology and figuring out how new programs work.
- You have a positive attitude and aren't afraid to share your ideas.
No college degree required. No professional AI development experience required.
If you've taught yourself creative software, built a social media page, experimented with AI tools, or completed interesting college projects, we'd love to see what you can do!
Why You'll Love Working Here
Your Ideas Actually Matter
You'll have the opportunity to work directly with company leadership and help develop our digital marketing strategy.
Learn Skills That Are in High Demand
Gain hands-on experience with artificial intelligence, digital advertising, video production, social media marketing, and automation.
Be Creative Every Day
This isn't a job where you'll be doing the exact same thing every day. You'll work on different creative projects, experiment with new technology, and help develop exciting campaigns.
Build Your Portfolio
Create real marketing campaigns, professional videos, graphics, and digital projects that demonstrate your skills.
Opportunity to Grow
As our company expands, we want this position to grow too. The right person could develop into a Marketing Manager, AI Marketing Specialist, or Digital Marketing Director.
Work With a Growing Industry
Help promote solar energy, roofing, and battery backup technology while learning about an evolving industry.
Experience & Education
We encourage applications from:
- College students and recent graduates
- Entry-level marketing and communications candidates
- Graphic designers and video editors
- Social media content creators
- Self-taught AI enthusiasts
- Creative individuals looking to start a career in digital marketing
Previous professional marketing experience is a plus, but not required.
Training and guidance will be provided as you learn our business, marketing platforms, and company processes.
How to Apply
Send us your resume and tell us a little about yourself!
Bonus points if you share something creative you've made!
It could be an Instagram Reel, TikTok, YouTube video, graphic design, school project, AI-generated image, website, or anything else that shows your creativity.
We don't need a perfect resume. We want to see your potential.
If you're creative, love technology, and want to turn your interest in AI and social media into a real career, we'd love to meet you!
Apply today and help us build the future of marketing at U.S. Solar Enterprise!
U.S. Solar Enterprise Inc. is an equal opportunity employer.
Pay: $22.00 - $28.00 per hour
Expected hours: 20.0 – 40.0 per week
Benefits:
- 401(k)
- Employee discount
- Flexible schedule
- Flexible spending account
- Paid time off
- Professional development assistance
- Referral program
Work Location: In person
Salary Context
This $45K-$58K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $178K across 1623 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 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Elysium Energy Solutions, 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 $211,950 based on 13,048 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($52K) sits 75% below the category median. Disclosed range: $45K to $58K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Elysium Energy Solutions AI Hiring
Elysium Energy Solutions has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Holtsville, NY, US. Compensation range: $58K - $58K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, 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 $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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