AI Architect & ML Leader (NLP/Recommenders)

Stride, Inc.

Indianapolis (IN)

À distance

USD 113 000 - 200 000

Plein temps

14 jours+
Générateur de candidature

Une candidature conçue pour ce poste — un CV et une lettre de motivation personnalisés qui correspondent à l’offre.

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Résumé du poste

Stride, Inc. is seeking an AI Architect to design and deliver production‑ready AI solutions across K12 and enterprise contexts.

You will lead a small team of AI Engineers, sometimes pulling in UX, front‑end, and subject‑matter experts to build end‑to‑end ML pipelines in cloud environments. The role emphasizes governance, data privacy, and actionable business impact, with direct supervision of 1–3 engineers, strong coding practices, and collaboration with Product, IT, and executives to align AI

Qualifications

  • Minimum: Bachelor’s degree in Computer Science, Math, Physics, Engineering or equivalent.
  • Experience designing and deploying ML models, especially NLP and recommender systems.
  • Proficiency with AWS, Azure, Docker, Kubernetes, and Terraform to build scalable environments.

Responsabilités

  • Drive conception, prototyping, and deployment of ML models (NLP, recommender systems).
  • Oversee production-ready AI systems using cloud ecosystems and IaC.
  • Mentor 1–3 AI Engineers and flexible contributors on projects.
  • Ensure governance, privacy, and compliance in AI solutions.
  • Align AI initiatives with organizational objectives and key stakeholders.

Connaissances

NLP
Recommender systems
Python
AWS
Azure
Docker
Kubernetes
Terraform
Leadership
Planning

Formation

Bachelor's degree in Computer Science / Math / Physics / Engineering
OREquivalent combination of education and experience

Outils

Docker
Kubernetes
Terraform
AWS
Azure
MLflow
Kubeflow

Description du poste

Stride, Inc. is seeking an AI Architect to design and deliver production‑ready AI solutions across K12 and enterprise contexts.

You will lead a small team of AI Engineers, sometimes pulling in UX, front‑end, and subject‑matter experts to build end‑to‑end ML pipelines in cloud environments. The role emphasizes governance, data privacy, and actionable business impact, with direct supervision of 1–3 engineers, strong coding practices, and collaboration with Product, IT, and executives to align AI

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