AI/ML Engineer

About Hilo Aviation

Hilo Aviation is building the AI-powered operating system for flight schools. Our platform touches student safety, regulatory compliance, and the daily operations of flight training programs across the country. We’re a small, serious technical team solving problems where “good enough” isn’t acceptable — and we’re growing deliberately.

The Role

We’re looking for an AI/ML Engineer who wants to build AI systems, not just call APIs. You’ll work directly with our CTO on developing and refining multi-agent AI workflows, model integrations, and intelligent automation that sits at the core of our platform.

This isn’t a research role. You won’t spend months benchmarking models or writing papers. You’ll ship working systems, iterate on them in production, and own outcomes — not just tasks.

We want someone at the top of this field — whether that means you’ve published work that demonstrates real intellectual depth in AI systems, or you’ve built and shipped production AI at a level that proves your capability. The bar is high. The opportunity to match it is real.

What You’ll Work On

•      Design and implement multi-agent orchestration workflows across our platform.

•      Build data pipelines that feed intelligent systems cleanly and reliably.

•      Integrate LLMs into product features with production-quality prompt engineering and evaluation.

•      Develop our IRIS risk assessment intelligence layer.

•      Help define how AI capability evolves across the platform as we scale.

What We’re Looking For

We’re looking for AI/ML engineers from two paths, and we’re genuinely open to both:

•      Graduates or researchers who have published relevant work, contributed to open-source AI systems, or built personal projects of significant technical depth — and who bring the kind of systems thinking that separates applied AI engineers from prompt experimenters.

•      Working engineers who have shipped production AI systems, can walk through the architecture and tradeoffs of real deliveries, and bring a track record of working AI in non-demo conditions.

Technically: strong Python fundamentals, exposure to ML frameworks (PyTorch, TensorFlow, or similar), solid understanding of LLMs and prompt engineering, and comfort working in cloud environments. TypeScript or Node.js is a plus. More important than stack familiarity is the ability to learn fast, think clearly under ambiguity, and ship things that actually work.

Mindset matters: we want someone who defaults to finding a way rather than waiting to be told one, who communicates openly about what they know and don’t know, and who cares about the quality of what they build — not just whether it works in demo conditions.

We move fast and we ship often. You're someone who drives toward delivery rather than getting comfortable in research mode — but you also know that speed without discipline creates the kind of debt that slows everything down. We build things right because we plan to build on top of them.

How We Hire

We don’t make offers based on résumés alone. Every candidate will complete a structured technical assessment, submit a portfolio or project review, and participate in an in-depth delivery walkthrough with our engineering team. We’re looking for evidence of how you think and what you ship — not just where you’ve been.

The Structure

Six-month contract with an optional path to full-time employment for the right person. We’re investing in the right people, and we expect that investment to convert. If you’re performing, we want you permanent — this structure gives both sides the confidence to move forward.

Hours: Full-time equivalent (40 hrs/week)

Rate: Competitive — based on demonstrated capability