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AI Engineer

Job in Mount Prospect, Cook County, Illinois, 60056, USA
Listing for: AMETEK, Inc.
Full Time position
Listed on 2026-09-12
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, DevOps, Software Architect
Salary/Wage Range or Industry Benchmark: 120000 - 140000 USD Yearly USD 120000.00 140000.00 YEAR
Job Description & How to Apply Below

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The AI Engineer designs, develops, and deploys AI/ML-powered software solutions that advance Atlas's business operations and product innovation. Working within the software engineering team, this role builds and integrates AI capabilities—including LLM-based tools, copilots, data pipelines, and cloud applications—in alignment with established architecture, engineering standards, and product roadmaps. The ideal candidate combines hands‑on technical depth across the full AI/ML lifecycle with strong collaboration skills, translating requirements from product and engineering leadership into scalable, reliable, production-grade solutions while upholding security, privacy, and responsible-AI practices.

Key Responsibilities:

Solution Development
  • Develop, test, and deploy AI‑powered software applications, including LLM‑based tools, copilots, and automation solutions
  • Develop and integrate APIs, services, and data pipelines that support AI functionality
  • Contribute to identifying and prototyping high‑value AI use cases in partnership with business, engineering, and lab‑services stakeholders
  • Translate defined requirements from product managers and engineering leadership into working solutions
  • Develop reliable, maintainable, and scalable software following team standards and established architectural guidelines
Deployment & MLOps
  • Support the deployment and maintenance of AI/ML applications in production environments
  • Implement and maintain monitoring, evaluation, and logging mechanisms for AI systems
  • Contribute to CI/CD pipelines and model/application lifecycle management
  • Support debugging, performance optimization, and system reliability
  • Work closely with the software engineering team, product stakeholders, and cross‑functional partners
  • Collaborate with the Software Engineering Manager and team on system design and implementation approaches
  • Participate in sprint planning, code reviews, and agile development processes
  • Communicate progress, risks, and technical trade‑offs clearly to the Software Engineering Manager and project stakeholders
Compliance & Quality
  • Follow established standards for security, privacy, and responsible AI usage
  • Support software validation, testing, and documentation per company processes (QMS where applicable)
  • Ensure compliance with internal development and deployment policies
  • Perform other duties as assigned
Requirements:

Education
  • Bachelor’s degree in Computer Science, Software Engineering, Data Science, Data Engineering, Electrical/Computer Engineering, or related field required
  • Master’s degree preferred (AI/ML, Computer Science, Software Engineering, or related)
Experience
  • 2+ years in software engineering, architecture, or applied data/ML engineering roles, with experience delivering AI/ML solutions (model development and/or LLM/RAG applications) into production environments
  • Hands‑on capability designing and building AI‑powered applications, including rapid prototyping through production deployment
  • Practical experience with the AI/ML lifecycle: data pipelines, evaluation, deployment, monitoring, maintenance, and MLOps
Technical Skills
  • Experience with LLM‑based applications (prompting patterns, tool/function calling, RAG, embeddings/vector databases, guardrails, and evaluation techniques)
  • Experience with cloud platforms (Azure or AWS), APIs/microservices, CI/CD pipelines, and secure deployment practices
  • Strong software design and modular development skills; ability to contribute to scalable, maintainable architectures and follow established engineering standards
  • Working knowledge of data security, privacy, and responsible AI practices (access control, governance, auditability)
  • Familiarity with software verification/validation, risk‑based testing, and…
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