Machine Learning Engineering jobs

Machine learning engineering in 2026 is mostly the craft of making models useful: fine-tuning open-weight checkpoints, wiring up inference, and watching the evals so a customer isn't the first to notice a regression. Far fewer teams train from scratch than the job titles imply. The roles that cluster here — ML Engineer, MLOps Engineer, Applied Scientist — share one description underneath: own the model after the notebook.

PyTorch is the assumed default; vLLM and Triton appear in half the serving stacks, with Kubernetes or Ray running most of the rest. Expect interview questions about quantization, LoRA fine-tunes, and what you'd do the week the eval numbers drift. Remote availability is genuinely good in this category, and US postings carry salary ranges more often than not.