Senior Platform and Machine Learning Operations Engineer

• Develops automated tests for reliability and regression coverage and contributes to reusable patterns, development standards, build automation, and continuous delivery practices.

• Owns assigned features or technical tasks by estimating effort, identifying risks and dependencies, meeting milestones, and collaborating across functions on development and troubleshooting.

• Documents processes and technical decisions, shares knowledge with peers, evaluates relevant technologies, and supports quality, security, and industry compliance.

Experience / Qualifications

• Relevant work experience or knowledge of the role
• Must be a team player able to work in a fast-paced environment with demonstrated ability to handle multiple competing tasks and demands
• Strong communication skills; oral, written and presentation
• Strong organization, planning and time management skills to achieve results
• Strong personal and professional ethical values and integrity
• Takes ownership of meeting goals and standards
• Proficient in Microsoft Office programs (Outlook, Word, PowerPoint, and Excel)
• Strong interpersonal & collaboration skills to work effectively with all levels of the organization including suppliers and/or external customers

Additional Responsibilities:

• Build and run core components of Sensata's Azure AI platform, including Azure AI Foundry, Azure OpenAI, the LLM gateway, telemetry and shared developer tools, under the direction of the AI Platform Lead.
• Build and maintain Dev/Test/Prod environments, CI/CD pipelines and infrastructure-as-code (Bicep/Terraform) so AI solutions are built, tested and released the same way every time.
• Implement MLOps/LLMOps pipelines for model and prompt deployment, evaluation, versioning, drift and performance monitoring, and rollback.
• Run production operations for platform services, including release management, observability, alerting and incident response.
• Implement identity and access controls, secrets management and responsible AI guardrails. Work with IT on the underlying cloud, network and identity foundations.
• Build reusable templates, SDKs, APIs and automation that help AI engineers and data scientists move from prototype to production quickly.
• Track and optimize platform usage, performance, reliability and cost.

Additional Qualifications:

• 5+ years of experience in software, platform, cloud or DevOps engineering, including hands-on work running production systems.
• Professional proficiency in spoken and written English.
• Hands-on experience deploying and operating ML or GenAI models in production.
• Strong Python skills. C# or Java a plus.
• Strong Azure experience. Azure AI Foundry, Azure OpenAI, Entra ID and API Management preferred.
• Hands-on experience with CI/CD (Azure DevOps or GitHub Actions), infrastructure-as-code (Bicep/Terraform) and containers (Docker, AKS or Azure Container Apps).
• Experience with MLOps/LLMOps tools and practices for model deployment, evaluation, versioning and monitoring.
• Working knowledge of identity and access management, secrets management, monitoring and logging.
• Strong troubleshooting skills and a track record of keeping production systems reliable.
• Bachelor's degree in Computer Science, Software Engineering, Information Systems or a related technical field.

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