An engineer who builds production systems that train and serve machine learning models at scale.
What machine learning engineers do
Machine learning engineers turn research prototypes into reliable systems. They build data pipelines, train and fine-tune models, deploy inference services, monitor performance and drift, and iterate on architectures to improve accuracy and latency.
Training path
Most US machine learning engineers hold a master’s or PhD in machine learning, computer science, or a related field. Some software engineers transition into the role by taking ML coursework and contributing to production model systems.
Tooling
Common tools include PyTorch, TensorFlow, JAX, MLflow, Kubeflow, Ray, Hugging Face, Triton, and Kubernetes. Cloud GPU instances on AWS, GCP, and Azure host model training and serving.
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Machine Learning Engineer starts with M and ends with R. Browse other professions along the same letter.
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