Senior Fullstack Software Engineer

November 6

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SurveyMonkey

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SaaS • B2B • Productivity

SurveyMonkey is a leading provider of online survey solutions, enabling users to create, distribute, and analyze surveys with advanced features. The platform supports a variety of use cases from product testing to customer satisfaction, employee engagement, and market research. Leveraging integrations with over 100 apps and built-in AI tools, SurveyMonkey offers customized forms and surveys for businesses in industries such as healthcare, education, finance, and more. With over 2. 4 million AI predictions daily, SurveyMonkey provides data-driven insights that help companies improve customer experiences, build better products, and drive growth. The service is trusted globally, with capabilities to cater to organizations of all sizes, offering both free and premium plans.

1001 - 5000 employees

Founded 1999

☁️ SaaS

🤝 B2B

⚡ Productivity

💰 $250M Private Equity Round on 2014-12

📋 Description

• 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. • 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.

🎯 Requirements

• 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. • Strong proficiency in frontend technologies (React, TypeScript, JavaScript, HTML, CSS). • Familiarity with CI/CD pipelines, containers (Docker), and orchestration (Kubernetes). • Understanding of MLOps concepts such as model deployment, monitoring, and lifecycle management. • Hands-on experience with AWS. • Strong collaboration skills and ability to work effectively with cross-functional teams. • Good documentation skills.

🏖️ Benefits

• medical, dental, vision, life, and disability insurance • 401(k) retirement plan • flexible spending & health savings account • paid holidays • paid time off • employee assistance program • other company benefits