Skill specialization

Machine Learning Engineer Jobs

Machine learning has moved from research desks to production platforms across every industry. ApTask places senior ML engineers with PyTorch, TensorFlow, LLM, and MLOps experience into applied AI teams — from Fortune 500 ML platforms to fast-moving GenAI startups. See open roles below.

11 live Machine Learning Engineer roles

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About Machine Learning Engineer roles at ApTask

Are these GenAI / LLM roles or classical ML?

Both. Some roles are GenAI, LLM or RAG work and others are classical ML (recommenders, forecasting, NLP). Search the board for 'GenAI', 'LLM' or 'RAG' to find the GenAI-specific ones; each posting states which it is.

What's the difference between ML engineer and data scientist here?

ML engineer: builds and deploys production models. Data scientist: designs experiments and validates models. Some roles blend both, especially at earlier-stage clients.

What ML platform experience is most valued?

Vertex AI, SageMaker, or Databricks ML for cloud platforms. MLflow or Weights & Biases for experiment tracking. Ray or Kubeflow for distributed training. Kubernetes for serving.

What bill rates should senior ML engineers expect?

Senior ML engineers with production experience bill $130-$220/hr. GenAI/LLM-focused engineers at the top of the market can bill higher.

How do Machine Learning Engineer rates compare with national wage data?

The closest occupation the U.S. Bureau of Labor Statistics tracks for Machine Learning Engineer roles is data scientists, which had a median annual wage of 120,230 US dollars in May 2025 (BLS Occupational Outlook Handbook, page last modified August 27, 2026). BLS reports the median wage of all employees in that occupation nationwide; the amounts elsewhere on this page are whatever each ApTask posting or FAQ answer states for itself, so read the BLS figure as national context rather than a like-for-like comparison.

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