Remote Machine Learning & AI Jobs

Remote machine learning roles split into two very different jobs: building models (training, evaluation, deployment) and building the systems around them (data pipelines, serving, evaluation harnesses) — and the second kind is growing fastest and hires from ordinary software backgrounds. Day-to-day work in a distributed team is experiment discipline: versioned datasets, written experiment logs, and reproduction steps a teammate eight time zones away can follow. The portable core is Python, one framework (PyTorch dominates research-adjacent work), and enough engineering to ship what you train.

As of the latest verification pass, 45 live worldwide machine learning & ai roles are open on the board — employers currently hiring include LatchBio, JUPUS and Circle, and the postings most often name Machine Learning, Python and Go.

Breaking in without a PhD: a reproduced paper with an honest write-up of what did not work, or a deployed model with a measured evaluation, both read as real experience. Contributing evaluation or data tooling to open ML projects substitutes for industry history, because reviewers can inspect it. Search “ML engineer” and “AI engineer” titles, which weight shipped systems over publications.

Hiring leans practical: a model-building take-home with documented decisions, a code review of your own experiment code, and written questions about evaluation design. Publication-counting interviews exist but concentrate in research labs.

Anchor expectations on the median advertised salary on this page: ML pay bands are wide — research-adjacent and infrastructure-heavy roles stretch well past it — and the figure counts employer-posted pay only.