Senior Software Engineer MLOps

What we’re looking for

We are seeking a Senior Software Engineer (MLOps) who can contribute to the operationalization of machine learning models and ML features within the product. In this role, you will be building the Next Generation ML Platform and also collaborating closely with data scientists and ML engineers to ensure models are deployed, monitored, and scaled effectively in production. This is a hands-on position where you’ll work across the stack and help bridge the gap between user experience and ML infrastructure. The Machine Learning Platform (MLP) team owns the complete ML operations pipeline and is responsible for building a machine learning platform that accelerates the efficient adoption of ML across all SurveyMonkey products.

What you’ll be working on

• Collaborate with data scientists to productionize ML models.
• Implement and maintain CI/CD pipelines for ML workflows.
• Contribute to model monitoring, data validation, and alerting systems.
• Support automation of model deployment, retraining, and versioning processes.
• Troubleshoot and resolve issues across ML infrastructure and frontend integrations.
• Build and maintain responsive, reusable, and performant UI components.
• Work with designers and product managers to translate requirements into intuitive user experiences.
• Integrate frontend applications with APIs and ML-driven services.
• Ensure accessibility, security, and performance best practices in frontend code.

 We’d love to hear from people with

• 5+ years of professional engineering experience, with exposure to both frontend and DevOps/MLOps domains.
• 3+ years of ML engineering experience using Python 3 in backend development and AWS for model deployment/serving.
• Familiarity with CI/CD pipelines, containers (Docker), and orchestration (Kubernetes).
• Strong understanding and hands-on experience in MLOps concepts such as model deployment, monitoring, and lifecycle management.
• Experience with LLMs, RAG based systems and agentic workflow is a plus.
• Hands-on experience with AWS.
• Strong collaboration skills and ability to work effectively with cross-functional teams.
• Good documentation skills.
• Bonus if you have exposure to ML frameworks (TensorFlow, PyTorch, scikit-learn).

SurveyMonkey believes in-person collaboration is valuable for building relationships, fostering community, and enhancing our speed and execution. While this role is remote, it may require in-person participation. You will be encouraged to attend company events throughout the year. These events will take place at a designated SurveyMonkey office or location.

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