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TalentHop
TalentHop

Senior AI Engineer - Data & MLOps (Teradyne, Remote)

Location

Remote restrictions apply
See all remote locations

Salary Estimate

N/AIconOpenNewWindows

Seniority

Senior

Tech stacks

AI
Testing
Automation
+23

Permanent role
a day ago
Apply now

This is a Fully Remote Job

About Our Client:

The organization specializes in global test and automation solutions that support next-generation technologies, particularly in electronics manufacturing. It addresses the challenge of ensuring device reliability and efficient product development by providing advanced test technology and automation tools. These solutions help manufacturers deliver products quickly and cost-effectively across various industries worldwide. The organization values a diverse, high-performance workforce and fosters an inclusive environment that supports innovation and continuous learning.

About the Opportunity:

The SENIOR AI ENGINEER - DATA & MLOPS role focuses on designing, building, and operationalizing machine learning and AI solutions within the IT organization. This position is responsible for developing robust AI applications such as predictive models, generative AI assistants, and intelligent automation, while ensuring their sustainability and reliability in production. The role bridges solution development with ongoing operational ownership, contributing to the enterprise’s capacity to maintain and improve AI capabilities that deliver measurable business impact.

Responsibilities:

  • Collaborate with IT and AI teams to translate business needs into ML/AI solutions.
  • Design, develop, train, evaluate, and deploy ML and generative AI models using enterprise AI platforms.
  • Integrate AI agents with enterprise data sources and APIs.
  • Apply rigorous experimentation and evaluation to deliver accurate and effective solutions.
  • Manage the transition of AI solutions from development to production, ensuring release readiness.
  • Implement full model lifecycle management including versioning, retraining, and deprecation.
  • Define criteria for model performance and coordinate solution tuning and remediation.
  • Partner with operations engineers to develop run-books and support materials.
  • Engineer reusable MLOps/LLMOps pipelines for automated model lifecycle management.
  • Build CI/CD, testing frameworks, and infrastructure-as-code for AI solutions.
  • Standardize experimentation, tracking, and deployment using appropriate tooling.
  • Establish automated evaluation and regression testing for AI models.
  • Develop technical standards, reference patterns, and reusable frameworks.
  • Define and document processes and playbooks for AI solution development and support.
  • Mentor and upskill team members in AI development and operations.

Requirements:

  • Extensive experience with ML/AI solution development across classical and generative AI.
  • Proficiency with Azure AI Foundry, Microsoft Copilot Studio, Google Vertex AI, and Snowflake Cortex AI.
  • Strong skills in integrating AI with enterprise data and systems.
  • Experience with MLOps/LLMOps automation, CI/CD, and infrastructure-as-code.
  • Ability to manage full model lifecycle and operational handoff.
  • Familiarity with experimentation, model evaluation, and deployment best practices.

Pay Range and Compensation Package:

  • The pay range and compensation package for this role will be determined based on the candidate's experience, skills, and other relevant factors.

Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin.

Note:

TalentHop is a recruitment partner of this role. Please note that all employment decisions, including candidate assessment, interviews, hiring, compensation, and employment terms, are made exclusively by the hiring employer.

About TalentHop

🔗Website
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