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About This Role
This is an on-site desk role in Hollywood, FL: email, quotes, and technical consulting for corporate clients. No hands-on assembly. Local applicants only.
BIZON, an industry-leading manufacturer of computers/servers for AI, is looking for a talented IT Support Specialist / Sales Engineer to join our growing team.
This is a rare opportunity to work every day with the most advanced computing hardware in the world — NVIDIA's latest GPUs, servers, water-cooled systems — and with clients like Stanford, MIT, Tesla, Samsung, Google, and Amazon.
If you're the person who reads spec sheets for fun, can explain a technical trade-off, and gets satisfaction from a quote where every number is right — this is the role for you.
You will own the technical sales process: from a client's first inquiry to the moment an order is confirmed, paid, and handed to the build team. You'll report to the Sales Manager and work closely with our engineering team.
What you'll do
- Handle a high volume of technical email: every day brings new clients, new workloads, and new questions.
- Translate client requirements ("we need a PC with 4x GPUs under $50K") into precise, compatible hardware configurations and formal quotes
- Manage multi-round quote revisions with clients via email and phone until the configuration is finalized
- Research and learn constantly: clients arrive with workloads, frameworks, and hardware you've never seen — you dig in, figure it out, and come back with a professional recommendation
- Use AI tools (Claude, ChatGPT, and similar) as a daily part of your workflow — for research, drafting, and checking your work
- Own the sales inbox: inquiries, follow-ups, order confirmations, payment verification, shipping details
- Coordinate order specifics with the build team; resolve issues with carriers and suppliers when they come up
- Handle corporate purchasing paperwork: POs, net terms, vendor registration forms, spec sheets.
What we require
- 3+ years of professional experience in a client-facing technical role — IT, systems integration, MSP, technical account management, technical pre-sales, or similar
- Solid understanding of computer hardware: you know what CPUs, GPUs, RAM, and storage do, how they fit together, and how to read a spec sheet. Experience with servers or GPU computing is a strong plus.
- Strong technical research skills. This is core to the job. When a client asks about a framework, model, or GPU you've never heard of, you find primary sources, verify the answer, and can defend your recommendation. You are comfortable not knowing something and fast at fixing that.
- Daily, confident use of AI tools is required. You already use them for research and writing, and you know where they're wrong and how to check.
- Must be very comfortable and effective in interacting via email and over the phone.
- Flawless written English. You'll write dozens of emails a day to procurement departments and senior engineers. Non-negotiable.
- Precision: prices, discounts, quantities, shipping addresses — one wrong digit costs real money. You double-check by habit, not by request.
- Judgment and ownership: you know what to resolve on your own and what to escalate to your supervisor.
- Ability to explain technical trade-offs clearly to both engineers and non-technical buyers
- Sales experience is a plus, not a requirement. Experience with corporate or institutional clients is.
- Must be able to pass a background check and drug test.
- Full-time, Monday–Friday, 9 AM–5 PM
- On-site: Hollywood, FL 33020
Benefits: We offer competitive salary, health insurance, paid time off, and a dynamic work environment. You’ll have opportunities to expand your skills in advanced computing (AI, GPU workstations, etc.) and work with a passionate team.
About BIZON
BIZON is an industry-leading provider of PC workstations, servers, and water-cooled systems. Our product line includes a wide range of desktops and servers for AI, video editing, 3D rendering/animation. 500+ companies and top universities trust BIZON (Stanford University, MIT, Berkeley, Tesla, Samsung, Google, Amazon, Oculus, Facebook, Qualcomm, and many more). More details: https://bizon-tech.com/
HOW TO APPLY:
Please submit your RESUME.
Please no phone calls regarding the job position.
BIZON is an Equal Employment Opportunity/Affirmative Employer.
Benefits:
- 401(k)
- Health insurance
- Paid time off
Work Location: In person
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 8,943 AI roles we're tracking, AI/ML Engineer positions make up 75% of the market. At BIZON, 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 $212,000 based on 11,866 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
BIZON AI Hiring
BIZON has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Hollywood, FL, US. Compensation range: $90K - $90K.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 median); Los Angeles (1,340 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 $253,100 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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