Senior Platform and Machine Learning Operations Engineer
Sensata Technologies, Inc. (company site, opens in a new tab)5+ yrsPuneOn-siteDirect career pageEst. 14–28 LPA
Posted 1d ago
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Reach people at Sensata Technologies, Inc.
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Sensata Technologies, Inc. you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, build, and maintain Sensata's Azure AI platform components including Azure AI Foundry, Azure OpenAI, and LLM gateway under AI Platform Lead.
- Develop and manage CI/CD pipelines, infrastructure-as-code (Bicep/Terraform), and MLOps/LLMOps pipelines for model deployment, monitoring, versioning, and rollback.
- Own production operations for platform services including release management, observability, alerting, incident response, and implement security controls and automation for rapid AI solution delivery.
Minimum Requirements
- 5+ years of experience in software, platform, cloud or DevOps engineering with hands-on production systems experience.
- Bachelor's degree in Computer Science, Software Engineering, Information Systems or related field.
- Strong experience with Python, Azure (including Azure AI Foundry, Azure OpenAI), CI/CD tools (Azure DevOps or GitHub Actions), infrastructure-as-code (Bicep/Terraform), and container technologies (Docker, AKS, Azure Container Apps).
- Work Experience Required: 5+ years; Professional proficiency in English.
Ideal Candidate Profile
- Experienced in running and supporting reliable production ML/GenAI deployments and platform operations focused on monitoring, troubleshooting, and incident response.
- Comfortable working in cloud-native environments using Azure's AI and infrastructure services, emphasizing automation and scalability.
- Able to collaborate cross-functionally with engineering, IT, and security teams to implement guardrails, identity management, and optimize platform cost and performance.