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About This Role
About the Company
Armada is the hyperscaler for the edge, delivering modular AI infrastructure from first deployment to AI factory with speed, scale and sovereignty. Named one of Fast Company's Most Innovative Companies and to the CNBC Disruptor 50, Armada's solutions are deployed in over 60 countries globally for organizations ranging from energy to defense.
With nearly $500 million in funding to date, Armada is backed by leading investors including Founders Fund, Lux, BlackRock and Microsoft (M12), alongside strategic partnerships with Microsoft, Dell, Palantir, NVIDIA, SpaceX, and Skydio. We are building the infrastructure layer for sovereign and edge AI - rugged, deployable compute for customers that cannot rely on centralized cloud.
Working at Armada means taking ownership, driving autonomy, and delivering impact. You'll tackle challenges that haven't been solved before and help build something transformative from the ground up. What you do here will not only define your career but help further Armada's mission to bridge the digital divide for customers around the world.
About the Role
The AI Factory team plays a critical role in driving Armada's growth across a focused set of high value, highly complex strategic accounts. These include AI focused data center operators, colocation providers, NeoCloud platforms, and select renewable energy operators that control land, power, or stranded energy assets suitable for large scale AI infrastructure. This team consists of senior, strategic sellers with a strong track record selling large scale deals, as well as deeply technical Customer Engineering, and Value Engineering, and Partnership teams.
We are hiring a Sales Coordinator to accelerate the team by providing key operational and administrative support across the sales team. You will ensure that our sales teams are focused and prepared, that our sales processes run smoothly, data is accurate, and communication between departments and clients is timely and professional.
Location. This role is remote-based on the continental US.
What You'll Do
Deal Team Support
- Track follow-ups owed by the AI Factory Account Executives and make sure every one closes
- Capture action items from deal meetings and chase them to completion
- Run the NDA process end to end: request, route for signature, track status, and confirm an NDA is in place before any engineering engagement
- Track documents and deliverables owed by counterparties, and manage data room access for prospective customers and partners
- Assemble and send collateral packages such as base designs, deployment materials, and presentations, and track what was sent to whom
- Maintain stakeholder trackers on multi-threaded deals so the team knows who is talking to whom at each counterparty
- Schedule customer meetings, site visits, and internal deal reviews across time zones
- Prepare meeting briefs and pre-read packets ahead of key customer and partner meetings
Travel and Events
- Book and coordinate travel for the AI Factory team
- Coordinate logistics for customer site visits and facility tours with customers, partners, and Armada engineering
- Coordinate logistics for AI Factory customer, investor, and executive events, including guest lists, invitations, vendors, and on-site details, in partnership with Armada's marketing and events team
- Process travel, event, and vendor expenses and invoices
CRM and Data
- Log offline meetings in Salesforce on behalf of the Account Executives, ensure all recorded calls, activities, and contacts are logged correctly, and keep AI Factory deal checklist fields current
- Improve forecast accuracy by ensuring all active deals are registered in Salesforce under the right time period, include validated exit criteria, and the appropriate forecast category
- Review Salesforce updates and call logs, and approve, correct, or reject them
- Keep offtake and financing partner contact records current
What Success Looks Like
- Follow-ups and meeting action items owed by the team close on time, including leadership referrals
- Every engineering engagement starts with an NDA in place
- Counterparty documents and data room access are never the reason a deal waits
- Salesforce reflects every meaningful customer interaction without Account Executives doing the data entry
- Travel, site visits, and events run without sellers managing the logistics
What We're Looking For
- 2-4 years of experience in sales coordination, transaction coordination, executive support, or project coordination, ideally at a B2B technology, infrastructure, or financial services company
- Highly organized, with a track record of managing many parallel threads and following through without reminders
- Clear, professional written communication with senior executives, customers, and investors
- Discretion with confidential deal and investor information
- Hands-on Salesforce experience; familiarity with Gong, Ironclad or DocuSign, virtual data rooms, and Chili Piper is a plus
- Comfortable using AI tools to automate routine work and reviewing their output for accuracy
- Flexible working hours to support a team spread across U.S., European, and Asia-Pacific time zones
Backgrounds We Value
- Sales, deal, or transaction coordination at a data center, energy, cloud infrastructure, capital projects, or infrastructure finance company
- Supporting a small, senior sales team in a high-growth or startup environment
- Executive assistant or chief of staff office experience on a fast-moving commercial team
Compensation & Benefits
For U.S. Based candidates: To ensure fairness and transparency, the starting base salary range for this role for candidates in the U.S. are listed, varying based on location experience, skills, and qualifications. In addition to base salary, this role will also be offered equity and subsidized benefits (details available upon request).
We use a geographic pay structure based on cost-of-labor markets.
- Tier 1 (e.g., SF Bay Area, NYC, Seattle): $30.61 – $38.26
- Tier 2 (most U.S. metro areas): $26.62 – $33.27
- Tier 3 (other cities): $25.28 - $31.61
Final compensation will be determined by experience, scope, and level, and may vary from the posted range.
Benefits
- Competitive base salary and equity
- Medical, dental, and vision (subsidized cost)
- Health savings accounts (HSA), flexible spending accounts (FSA), and dependent care FSAs (DCFSA)
- Retirement plan options, including 401(k) and Roth 401(k)
- Unlimited paid time off (PTO)
- 14 paid company holidays per year
#LI-SM1
#LI-Remote
You're a Great Fit if You're
- A go-getter with a growth mindset. You're intellectually curious, have strong business acumen, and actively seek opportunities to build relevant skills and knowledge
- A detail-oriented problem-solver. You can independently gather information, solve problems efficiently, and deliver results with a "get-it-done" attitude
- Thrive in a fast-paced environment. You're energized by an entrepreneurial spirit, capable of working quickly, and excited to contribute to a growing company
- A collaborative team player. You focus on business success and are motivated by team accomplishment vs personal agenda
- Highly organized and results-driven. Strong prioritization skills and a dedicated work ethic are essential for you
Equal Opportunity Statement
At Armada, we are committed to fostering a work environment where everyone is given equal opportunities to thrive. As an equal opportunity employer, we strictly prohibit discrimination or harassment based on race, color, gender, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other characteristic protected by law. This policy applies to all employment decisions, including hiring, promotions, and compensation. Our hiring is guided by qualifications, merit, and the business needs at the time.
Unsolicited Resumes and Candidates
Armada does not accept unsolicited resumes or candidate submissions from external agencies or recruiters. All candidates must apply directly through our careers page. Any resumes submitted by agencies without a prior signed agreement will be considered unsolicited and Armada will not be obligated to pay any fees.
Salary Context
This $52K-$79K 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 ARMADA, 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 $211,950 based on 13,048 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300. This role's midpoint ($65K) sits 69% below the category median. Disclosed range: $52K to $79K.
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.
ARMADA AI Hiring
ARMADA has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $79K - $79K.
Remote Work Context
Remote AI roles pay a median of $188,000 across 2,316 positions. About 6% of all AI roles offer remote work.
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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