Machine Learning Engineer

THE COMPANY

Careerminds is a leader in career transition and coaching solutions, helping organizations support employees through change while enabling workforce growth and development. Our product portfolio includes market-leading Career Transition and Coaching Services as well as Progression, our application for Career Frameworks and progression planning.

THE ROLE

We're growing our machine learning team. We're looking for Machine Learning Engineers who own products end to end — from the problem, to production, to the metric that proves it worked.

This role exists because of how we build. A small product strategy team sets direction and priorities; engineers own the work end to end — discovery, design, build, ship, and the result. You'll have the autonomy of a founder inside your domain and the accountability that comes with it.

That accountability includes the unglamorous half of ML. You own the experiment that doesn't pan out and the call to kill it, not just the launch. We'd rather you run four honest experiments and ship the one that works than ship four things that all look fine on a dashboard.

AI-native development isn't an aspiration here — it's the baseline. Our engineers ship with Claude Code and Claude Design as their default tools, and the leverage that creates is why one engineer can own a product end to end.

We want people already working this way who want to push the ceiling higher, not people who are curious about AI. In the interview we'll ask you to show us the trail: repos, PRs, or shipped work you built this way.

This is a 100% remote/work-from-home role.

THE KEY RESPONSIBILITIES

Depending on area of focus

Canonical data and entity resolution

• Canonical datasets for titles, companies, skills, and industries — the layer every application depends on. Content-addressed IDs, faceted taxonomies, alias graphs accumulated across tens of millions of rows.
• Rules-based resolution pipelines with LLM esc