Applied AI Engineer - ML Ops & Edge Deployment

Archer; Florida; Sur place; USD 120 000 - 180 000; Plein temps

Résumé du poste

MANTECH in Doral, FL is seeking a motivated Applied AI Engineer to design, deploy, and optimize scalable AI/ML models across cloud, on‑premise, and edge environments. The role emphasizes integration of data streams, automation of training workflows, and strong documentation practices.

Required are 5+ years in analytics or a related field (or equivalents), expertise with PyTorch/TensorFlow, Python and C++, and experience with Docker/Kubernetes and MLOps. Security clearance is required.

Qualifications

• Bachelor’s degree required with 5+ years in advanced analytics or data science roles; or advanced degrees with years of relevant experience.
• Proven experience deploying ML models and AI apps using modern frameworks (PyTorch, TensorFlow) and strong software development background.
• Experience with cloud architectures, containerization, and MLOps deployment pipelines; ability to author architecture docs.

Responsabilités

• Design, develop, and deploy scalable AI/ML models to solve operational challenges.
• Orchestrate AI/ML pipelines, integrate data streams, and automate training/evaluation workflows.
• Collaborate with cross‑functional teams to define AI architecture standards and baselines.
• Evaluate models and optimize performance across cloud, on‑premise, and edge environments.
• Maintain configurations and documentation for AI systems and models.
• Evaluate new AI frameworks and tooling for continuous improvements.

Connaissances

PyTorch

TensorFlow

Python

C++

APIs

Docker

Kubernetes

MLOps

Formation

Bachelor’s degree in Data Science/CS/Math/Statistics

Master’s degree (preferred)

PhD (preferred)

Associate’s degree withExperience

High School Diploma with Experience

Outils

Docker

Kubernetes

Description du poste

MANTECH in Doral, FL is seeking a motivated Applied AI Engineer to design, deploy, and optimize scalable AI/ML models across cloud, on‑premise, and edge environments. The role emphasizes integration of data streams, automation of training workflows, and strong documentation practices.

Required are 5+ years in analytics or a related field (or equivalents), expertise with PyTorch/TensorFlow, Python and C++, and experience with Docker/Kubernetes and MLOps. Security clearance is required.