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Company Description

LunarTech is a frontier Enterprise operating at the intersection of Artificial Intelligence, Data Science, and the critical sectors that power modern countries. We design and deploy applied AI systems that move beyond prototypes into real operational environments, where reliability, security, and measurable outcomes matter.

LunarTech’s work spans the full lifecycle of modern AI—strategy, research, engineering, deployment, and continuous improvement—across domains where decisions carry real-world consequences:

• Artificial Intelligence & Data Science: Production-grade ML systems, generative AI, model evaluation, MLOps, and applied research that translates into deployable capabilities.
• Education (LunarTech Academy): Certified programs and bootcamps that train professionals to build and deploy real systems, bridging the gap between coursework and industry-grade execution.
• Enterprise & Institutional Enablement (LunarTech Enterprises): Corporate and institutional training designed to raise internal capability, accelerate adoption, and establish repeatable AI operating practices.
• Healthcare & clinical-adjacent applications: Decision support, workflow optimization, and responsible AI implementations designed for high-stakes environments with strict standards for privacy and safety.
• Manufacturing & industrial engineering: AI-enabled process intelligence, quality systems, predictive maintenance, and automation to improve throughput, reliability, and cost efficiency.
• Law & Legal AI: Workflow automation, document intelligence, and human-in-the-loop systems that increase speed and precision while respecting compliance and audit requirements.
• Aerospace & advanced systems: Data-driven engineering and AI-assisted analysis for complex, safety-critical systems where performance and verification are essential.

Through LUNARTECH Labs, we build custom AI and data solutions end-to-end, from data pipelines and model development to deployment, monitoring, and iteration. We also develop and maintain Phoenix, our AI-powered productivity and automation platform with 200+ advanced tools supporting research, analysis, content workflows, operations, and internal execution.

Across everything we do, LunarTech is built around a single principle: turning frontier AI into practical, secure, and scalable capability—so organizations can operate faster, smarter, and with greater strategic leverage.

Role Description

The AI Engineering Apprentice is a remote, part-time position. The role involves collaborating with cross-functional teams to support the design, development, and implementation of AI-powered solutions.

Responsibilities include analyzing data, building prototypes, assisting with project management tasks, applying engineering principles, and contributing to product development processes in line with industry requirements. Apprentices will work closely with senior engineers and gain valuable hands-on experience while participating in innovative projects with real-world applications.

Why this apprenticeship is a career accelerator

LunarTech operates at the frontier of applied AI and frontier technologies — where real constraints, real users, and real stakes meet cutting-edge engineering. You won’t be learning in the abstract. You’ll be learning by building.

Our work spans high-impact domains such as:

• AI engineering and production-grade ML systems
• Voice AI and conversational agents
• Legal AI and workflow automation
• Aerospace and advanced systems
• Healthcare and clinical-adjacent applications
• Manufacturing and industrial engineering use cases

We build in-house, end-to-end. That means you’ll see and contribute to the full stack of what it takes to ship: product thinking, UI/UX, data pipelines, model experimentation, evaluation, deployment, tooling, and iteration. We don’t outsource the hard parts — we own them.

This program is intentionally selective. We protect our intellectual property, we move fast, and we expect focus. In return, you get an environment designed to create what we call “20X engineers”: builders who can take ambiguous problems, execute with discipline, and reliably deliver outcomes.

If you are serious about accelerating your trajectory, this apprenticeship is built to compress years of industry learning into months. It’s a bridge from “academy-level knowledge” to “industry-grade execution” — with mentorship, feedback loops, and real deliverables.

What we invest in you:

• Structured mentorship and direct guidance from senior engineers
• Hands-on projects with clear standards and measurable outcomes
• Tools, playbooks, and internal guides to help you move fast
• Access to AI credits and an engineering environment built for experimentation
• Collaboration with a high-caliber network of builders across the organization

These openings are limited. When they open, strong candidates move quickly — because the upside is obvious.

Qualifications

• Strong communication skills to collaborate with team members and stakeholders effectively.
• Excellent analytical skills for problem-solving and identifying solutions in data and engineering tasks.
• Basic understanding or experience with project management to assist in coordinating tasks and meeting deadlines.
• Knowledge in manufacturing engineering with exposure to industry processes and practices.
• Familiarity with mechanical engineering principles to contribute to certain design and development tasks.
• Willingness to learn and work in a fast-paced, innovative environment with emerging technologies.
• Educational background in Engineering, Data Science, AI, or a related field is preferred.
• Strong organizational skills and the ability to manage multiple tasks simultaneously.

Screening Questions

To ensure the program is a good fit, we ask candidates to confirm the following upfront:

• Bachelor’s degree completed.
• You understand this is an unpaid, learning-first 6-month apprenticeship focused on mentorship and real-world experience (not a paid employment role).
• You’re comfortable completing a practical technical assignment as part of the evaluation process.
• You can commit roughly 25 hours per month (flexible scheduling) and attend mandatory mentorship + presentation sessions.
• You’re willing to sign onboarding documents prior to starting (including MoU, NDA, and related agreements).