Technical Trainer - AI Infrastructure Products (Part-time)

Armada • United States (Remote), CA

26d • $110 - $140 • Hybrid

About The Position

Armada is seeking a patient, articulate, and technically fluent Part-Time Technical Trainer to join their team on an on-demand basis. This role is focused on technical marketing, requiring understanding and confident use of Armada's GPUaaS platform and ecosystem, but not development on it. The primary responsibilities include building customer-centric demo content that replaces engineering-centric recordings with relatable, use-case-driven flows, and delivering hands-on, guided training sessions at customer sites globally. The work is project-based, averaging roughly one week per month, and is ideal for an experienced professional seeking engagement without a full-time commitment. This is a non-converting contract engagement with variable hours and travel, suitable for seasoned technical trainers or solutions engineers looking for meaningful part-time work.

Requirements

• 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.
• Demonstrated ability to explain complex technical concepts clearly and concisely to both technical and non-technical audiences.
• 3+ years of formal training, instructional design, or technical enablement experience; curriculum development experience required.
• 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.
• 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.
• 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.

Nice To Haves

• 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.

Responsibilities

• Design, develop, and deliver hands-on technical training for enterprise customers, focusing on interactive sessions where customers execute steps in their own environments.
• 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 the audience, primarily hands-on technical practitioners and their managers (senior manager / director level).
• 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.
• Own the transition from engineering-centric demos to customer-centric ones by learning product flows, setting up environments, recording polished walkthroughs with clear voiceover, and publishing relatable content.
• Create and maintain a library of enablement artifacts, including 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, serving as both training material and standalone content.
• 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.
• 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 the platform.
• Gather feedback during training engagements and relay actionable insights to Product and Customer Success teams.
• 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.

Benefits

• Truly flexible, on-demand engagement — ideal for an experienced professional seeking meaningful part-time work without a full-time commitment.
• $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.

What This Job Offers

• Job Type: Part-time
• Career Level: Mid Level
• Education Level: No Education Listed