Technical Trainer - AI Infrastructure Products (Part-time)

About the Role

We are seeking a patient, articulate, and technically fluent Part-Time Technical Trainer to join our team on an on-demand basis. This role sits closer to technical marketing than software development — you will need to understand and confidently use our GPUaaS platform and surrounding ecosystem, but you are not expected to develop on top of it. Your primary focus will be two-fold: (1) building customer-centric demo content that replaces engineering-centric recordings with relatable, use-case-driven flows, and (2) delivering hands-on, guided training sessions at customer sites around the world. Work is project-based, averaging roughly one week per month, and is ideal for an experienced professional who wants to stay engaged without a full-time commitment. 

This is a non-converting contract engagement. Hours and travel are not guaranteed week-to-week; when a training trip is scheduled, you go — when it is not, there is no work. The predictable portion of the role is demo and curriculum creation; the training delivery side fluctuates. If you are a seasoned technical trainer or solutions engineer looking for meaningful part-time work, this role is built for you. 

 

Location: This role is remote within the continental United States. 

 

What You'll Do (Key Responsibilities)

Customer Training & Enablement 

• Design, develop, and deliver hands-on technical training for enterprise customers — not slide presentations, but guided, interactive sessions where customers execute steps in their own environments with you by their side. 
• Travel globally to customer sites (domestic and international) to conduct in-person training; deliver remote sessions when travel is not required. 
• Tailor curriculum and pacing to your audience — primarily hands-on technical practitioners and their managers (senior manager / director level); this is not a C-suite audience. 
• Conduct needs-assessments before each engagement to align training content with customer use cases and success metrics. 
• Provide post-training follow-up support, Q&A sessions, and supplementary materials to reinforce learning. 

Content Creation & Demo Production 

• Own the transition from engineering-centric demos to customer-centric ones: learn Armada’s identified product flows, set up the environment, record polished walkthroughs with clear voiceover, and publish content that customers can relate to. Assume net-new creation — demos go stale approximately every three months as new features ship. 
• Create and maintain a library of enablement artifacts: quick-start guides, how-to articles, sample code notebooks, architecture diagrams, and slide decks. 
• Build step-by-step lab flows that customers can follow independently; the same flows should double as training material, creating a single content library that serves both purposes. 
• Collaborate with Product and Engineering to translate new feature releases into clear, customer-ready training content. 
• Leverage AI productivity tools (e.g., AI video editors, scripting assistants, image generation, and documentation tools) to accelerate content production. 

Technical Demonstrations & Evangelism 

• Deliver live technical demos at customer discovery calls, webinars, conferences, and partner events. 
• Act as a credible technical voice, demonstrating GPU workload provisioning, cluster management, performance tuning, and cost optimization on our platform. 
• Gather feedback during training engagements and relay actionable insights to Product and Customer Success teams. 

Continuous Improvement 

• Keep curriculum current with evolving GPUaaS product features, industry frameworks (PyTorch, CUDA, Kubernetes, etc.), and emerging AI/ML trends. 
• Track training effectiveness through assessments, surveys, and usage analytics; iterate content based on results. 
• Contribute to a knowledge base and internal trainer certification program as the team scales. 

 

Required Qualifications

Technical Expertise

• 10–15 years of overall professional experience in technical roles, with at least 3 years focused on cloud infrastructure, GPU computing, or HPC environments. 
• Proficiency with Linux, containers (Docker/Kubernetes), and cloud CLI tooling. 
• Working knowledge of at least one deep-learning framework (PyTorch, TensorFlow, JAX) and GPU programming fundamentals (CUDA, cuDNN, or similar). 
• Comfortable reading and writing Python; ability to build clear, reproducible Jupyter notebooks for instructional use. 

Training & Communication 

• Demonstrated ability to explain complex technical concepts clearly and concisely to both technical and non-technical audiences — articulateness is non-negotiable. 
• 3+ years of formal training, instructional design, or technical enablement experience; curriculum development experience required — not just delivery. 
• Exceptional verbal and written English communication skills; comfortable presenting to groups of all sizes. 
• Patient, methodical teaching style — able to slow down, take a breath, and guide customers through technical content step by step without frustration. 

 

Content Production 

• Experience producing instructional or demo videos (screen recording, voiceover, light editing) using tools such as Camtasia, Loom, DaVinci Resolve, or equivalent. 
• Proficiency with AI productivity tools — e.g., AI writing assistants, automated transcription/captioning, AI image/diagram generators, and prompt-based video editors. 
• Strong documentation skills; ability to produce polished slide decks, technical guides, and quick-reference cards. 

Logistics 

• Must hold a valid passport; travel is global and may include international customer sites. 
• Comfortable with an on-demand travel schedule — when a training engagement is scheduled, you are expected to travel; there is no guaranteed frequency or fixed number of trips per month. 
• Reliable home-office setup with high-speed internet for remote training delivery. 

 

Preferred Qualifications:

• Prior experience in a cloud/HPC vendor, GPU OEM, or AI infrastructure company. 
• Familiarity with MLOps practices (MLflow, W&B, Kubeflow) and distributed training paradigms. 
• Certifications in relevant platforms: AWS, GCP, Azure, NVIDIA DLI, Kubernetes (CKA/CKAD), or similar. 
• Experience with LMS platforms (Docebo, Teachable, Moodle) for publishing and tracking online courses. 
• Background in developer relations, technical sales engineering, or solutions architecture. 

 

What We Offer:

• Truly flexible, on-demand engagement — ideal for an experienced professional seeking meaningful part-time work without a full-time commitment. Hours are not guaranteed week-to-week; this role will not convert to full-time. 
• $110–$140/hr contract rate. 
• Full travel and expense reimbursement for all customer-site visits. 
• Access to our full GPUaaS platform for self-directed learning, demo prep, and content creation. 
• Collaborative team culture with direct access to Product and Engineering leadership. 
• Opportunity to grow with a fast-moving company at the forefront of AI infrastructure. 

 

Compensation

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 below, varying based on location experience, skills, and qualifications.

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