Interested in this AI/ML Engineer role at Tmi Universal Sports?
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About This Role
This Magazine operates at the intersection of technology, media, and culture, building a platform that connects innovation with lifestyle, business, and global audiences. As we expand our digital ecosystem, we are seeking a skilled AI Coding Engineer to support platform development and intelligent system integration.
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Role Overview
We are looking for an full stack engineer to in build and optimize the ITS Magazine platform. This role involves working on AI\-driven features, UI/UX, backend systems, and scalable infrastructure to enhance user experience, content delivery, and automation.
You’ll collaborate with a forward\-thinking team focused on media, marketing, and emerging technology, helping shape how audiences interact with content and brands.
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Key Responsibilities
- Develop and integrate AI\-powered features into the ITS Magazine platform
- Assist with backend architecture, APIs, and system scalability
- Build or implement models for content recommendations, automation, and user engagement
- Collaborate with design and marketing teams to align technical solutions with user experience
- Optimize platform performance, speed, and reliability
- Stay current with emerging AI tools, frameworks, and best practices
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Preferred Qualifications
- Experience in AI/ML development, software engineering, or related fields
- Proficiency in languages such as Python, JavaScript, or similar
- Familiarity with AI frameworks (e.g., TensorFlow, PyTorch, OpenAI APIs, etc.)
- Experience with web development, APIs, and cloud infrastructure
- Ability to work independently and within a collaborative environment
- Strong problem\-solving skills and attention to detail
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What This Opportunity Offers
- Work at the intersection of AI, media, and culture
- Opportunity to help build and scale a growing digital platform
- Exposure to projects across technology, marketing, and content ecosystems
- Flexible work structure with growth potential into long\-term roles
- Access to a network spanning media, tech, luxury, and business sectors
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How to Apply
Please reply with:
- Your resume or portfolio
- Links to relevant projects or GitHub
- A brief summary of your experience with AI and platform development
Qualified candidates will be contacted with next steps After answering these question:
Industry Knowledge and Vision:
What is your understanding of the media, entertainment, technology, sports, marketing, arts, finance, and luxury sectors that ITS Magazine serves?
Does an opportunity that combines modest compensation with long\-term equity and partnership potential appeal to you? Why or why not?
How do you believe your software engineering and technical expertise could elevate not only ITS Magazine, but other platforms we are developing?
Technology and Product Development
In your opinion, which platform(s) offers greater advantages for scalability and flexibility? Please explain your reasoning.
If you were designing your ideal platform from scratch, what would it be and why? (It does not need to be related to ITS Magazine.)
What technologies, frameworks, or AI tools do you believe will have the greatest impact on digital media platforms over the next five years?
Leadership and Team Development
Leadership and team\-building are critical components of this role. Please describe your experience developing, managing, or mentoring teams.
How would you describe your management style?
How do you handle disagreements regarding product direction or technical decisions?
Have you previously led projects from concept to launch? If so, please provide examples.
If selected, how would you approach building and managing an engineering team as the platform grows?
Long\-Term Vision:
If you joined ITS Magazine tomorrow, what would your first 90 days look like, and what would you prioritize?
We look forward to learning more about your experience, leadership style, and long\-term goals. Thank you again for your interest, and we look forward to your response.
Pay: $20\.00 \- $40\.00 per hour
Benefits:
- Flexible schedule
Work Location: Hybrid remote in New York, NY 10011
Salary Context
This $41K-$83K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Tmi Universal Sports, 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 $218,750 based on 3,817 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,150. This role's midpoint ($62K) sits 71% below the category median. Disclosed range: $41K to $83K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Tmi Universal Sports AI Hiring
Tmi Universal Sports has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $83K - $83K.
Location Context
AI roles in New York pay a median of $220,000 across 1,045 tracked positions.
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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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