Senior Data & AI Engineer: Hands-on AI & Automation Builder

Daimler Truck North America

Portland (ME)

Sur place

USD 117 000 - 150 000

Plein temps

Il y a 4 jours
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Avantages offerts par ce poste

Annual bonus
401k match
4 weeks vacation
Holidays
Parental leave
Employee assistance
Healthcare plans
Onsite fitness
Tuition assistance
Volunteer PTO
Disability plans

Résumé du poste

Daimler Truck North America is seeking a senior data and AI engineer to design, build, and deploy AI/ML and automation solutions across the BDAT team. You will collaborate closely with business teams, IT, and the Data Intelligence Hub to turn prototypes into production-ready capabilities and foster a scalable data-driven culture.

You will coach teams, promote best practices in CI/CD, testing, and documentation, and share expertise across the organization to enable sustainable data and AI

Qualifications

  • Senior data/AI engineer with hands-on development experience.
  • Proven ability to translate business objectives into working AI/analytics solutions.

Responsabilités

  • Design, build, and deploy AI/ML and automation solutions for high-impact initiatives.
  • Co-develop with business teams to own, enhance, and sustain what is built.
  • Translate business objectives into production-ready solutions and rapid proofs of concept.
  • Partner with IT and Data Intelligence Hub to implement self-service analytics, automation, and AI tools.

Connaissances

AI/ML engineering
Data analytics
Automation
CI/CD pipelines

Outils

Snowflake
Snowflake Cortex
Microsoft Copilot
Copilot Studio
LibreChat
Power Platform
GitHub

Description du poste

Daimler Truck North America is seeking a senior data and AI engineer to design, build, and deploy AI/ML and automation solutions across the BDAT team. You will collaborate closely with business teams, IT, and the Data Intelligence Hub to turn prototypes into production-ready capabilities and foster a scalable data-driven culture.

You will coach teams, promote best practices in CI/CD, testing, and documentation, and share expertise across the organization to enable sustainable data and AI

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