Machine Learning Engineer

About the role

OUR MISSION AND WHY IT MATTERS

We are on a mission to make humans the strongest security layer.

Human risk remains one of the biggest vulnerabilities and traditional awareness training is not enough. We take a different approach by combining AI-driven personalization, real threat detection, and behavioral science to actively protect people and organizations.

We don't just simulate risks. We build the tools that detect and stop them.

WHY THIS ROLE MATTERS

Our internal AI development team is a small, fast-moving task force and the go-to experts for ML across Hoxhunt's products. We build and maintain a shared LLM SDK that lets product teams ship AI-powered features without worrying about telemetry, cost tracking, or model management, and we own the most complex AI features ourselves, including the multimodal pipelines, multi-step agentic systems, and specialist ML models that go beyond what any single product team can handle alone.

We're growing because demand is outpacing our capacity. AI is now business-critical to everything we ship, and we need another strong engineer to help us keep up.

As a Machine Learning Engineer on the AI development team, you'll embed with product teams to tackle hard problems, ship solutions, and move on to the next challenge. One month you might be minimising unit costs on a pipeline serving millions of users; the next, you're building a threat detection model with its own training loop and data collection pipeline. The problems are technically demanding and the impact is real.

WHAT YOU'LL OWN AND DRIVE

- Design, develop, and maintain AI features and ML models serving millions of end users

- Build and maintain scalable APIs that integrate models directly into our products

- Ensure the reliability, scalability, and observability of our AI systems

- Collaborate cross-functionally with product teams and PMs to scope and execute complex projects

- Take end-to-end ownership of initiatives from the initial idea all the way to execution

WHAT SUCCESS LOOKS LIKE

- In your first 3 months you'll: Ramp up on our tech stack, begin shipping features, and actively contribute to project planning and execution.

- By month 6 you'll: Drive end-to-end projects, contribute to architectural decisions, and operate as a trusted core team member.

WHAT MAKES YOUR THRIVE HERE

You have:

- At least 3 years of software engineering experience in production environments

- Strong Python skills and solid software engineering fundamentals, including writing production-grade code

- Hands-on experience with LLMs, generative AI systems, and ML feature development in production

- Experience with at least one major cloud platform like GCP, AWS, or Azure

- A builder mindset, meaning you love to ship fast, iterate, and move on without needing tightly defined problems