AI & ML Engineering · USA

AI / Machine Learning Engineers
across the USA

Contract, contract-to-hire, and permanent AI and Machine Learning engineers who design, train, and deploy models in production. Python, TensorFlow, PyTorch, MLflow, and LLM integration specialists.

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Role Overview

What AI / Machine Learning Engineers do

AI and Machine Learning engineers bridge the gap between data science research and production software engineering. They build the infrastructure and pipelines that take trained models from a notebook into scalable, reliable, production systems.

Demand for ML engineers in the US has accelerated sharply with the growth of LLM applications, RAG architectures, and AI-integrated product features. Companies need engineers who can not only train models, but deploy, monitor, and maintain them at scale — including cost and latency optimisation.

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Model training, fine-tuning, and evaluation pipelines

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LLM integration, RAG architecture, and prompt engineering

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MLOps — model versioning, monitoring, and CI/CD for ML

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Feature engineering and data preprocessing at scale

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Cloud ML deployment (AWS SageMaker, Azure ML, Vertex AI)

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Model interpretability, fairness, and safety considerations

Skills We Source

PythonTensorFlowPyTorchHuggingFaceLangChainscikit-learnMLflowPandas / NumPy

Common Tools

AWS SageMakerVertex AIAzure MLDatabricksAirflowRayKubernetesOpenAI API

Hiring in the USA

Demand for AI / Machine Learning Engineers in the US technology market is driven by cloud adoption, digital transformation, and the growing complexity of software delivery. Contract and permanent positions are both common — contract roles typically run 3–24 months, while permanent hires represent long-term team investment.

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