AI Deployment Engineer

Description

AI Deployment Engineer

We are looking for an AI Deployment Engineer to take machine learning and AI models from prototype to production. This role owns the pipelines, infrastructure, and monitoring that make AI reliable, scalable, and secure in a real environment.

Responsibilities

+ Deploy, scale, and monitor machine learning and generative AI models in production

+ Build and maintain MLOps pipelines for training, deployment, and versioning

+ Containerize and orchestrate workloads using Docker and Kubernetes

+ Integrate models and APIs into applications and business workflows

+ Optimize model performance, latency, and infrastructure cost

+ Implement monitoring, logging, and alerting for deployed models

+ Collaborate with data scientists and engineers to product ionize solutions

+ Apply security and governance standards to AI systems and data

Requirements

Required Qualifications

+ 3 or more years in ML engineering, MLOps, Dev Ops, or a related field

+ Strong Python skills and experience deploying models to production

+ Hands on experience with Docker and Kubernetes

+

Experience with a major cloud platform (AWS, Azure, or GCP)

+ Familiarity with CI/CD pipelines and infrastructure as code

Preferred Qualifications

+ Experience deploying large language models or working with frameworks such as Lang Chain

+ Familiarity with vector databases and retrieval augmented generation

+

Experience with model serving tools such as MLflow, Sage Maker, or Vertex AI

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