
1001 - 5000 employees
☁️ SaaS
🤝 B2B
SaaS • B2B
SurveyMonkey is an online survey and forms platform that lets organizations and individuals build, send, and analyze surveys to collect feedback and insights. The platform offers 500+ templates, AI-assisted survey creation, a global audience panel of 335M+ respondents, analytics and integrations, and enterprise-grade features for secure, large-scale survey programs. It’s used across customer experience, employee feedback, market research, event registration, and more; the company markets itself as a continuous insights/SaaS platform serving 260K+ organizations worldwide.
🔥 28 minutes ago
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1001 - 5000 employees
☁️ SaaS
🤝 B2B
SaaS • B2B
SurveyMonkey is an online survey and forms platform that lets organizations and individuals build, send, and analyze surveys to collect feedback and insights. The platform offers 500+ templates, AI-assisted survey creation, a global audience panel of 335M+ respondents, analytics and integrations, and enterprise-grade features for secure, large-scale survey programs. It’s used across customer experience, employee feedback, market research, event registration, and more; the company markets itself as a continuous insights/SaaS platform serving 260K+ organizations worldwide.
• Build and maintain robust ML systems using Python (Pandas/NumPy, PyTorch/transformers) to support efficient ML operations • Design ML cloud infrastructure using AWS services, ensuring the platform is built for reuse, scalability, and high-volume throughput • Collaborate with application engineers to integrate, test, and monitor ML model services across SurveyMonkey’s microservices architecture • Act as a consultant to internal feature teams, educating and influencing decisions regarding ML tooling and infrastructure • Incorporate telemetry into the platform for complex failure mode analysis, ensuring real-time reliability for millions of daily survey responses • Serve as a technical leader and mentor, championing high standards in coding, documentation, and architectural best practices to foster the professional growth of junior engineers on the MLP team
• 8+ years of professional ML development experience with a proven track record of designing and implementing ML infrastructure in AWS • Mastery of ML concepts (supervised/unsupervised learning) and deep understanding of Large Language Models (LLMs) and NLP • Expert-level Python skills and experience with high-scale data processing (PySpark, etc.) • Comfortable with Unix/Linux systems and experienced in deploying end-to-end solutions for real-time applications (spam detection, personalization, ranking) • Bachelor’s Degree in Computer Science, Data Science, Software Engineering, Mathematics, Statistics, or a related quantitative field
• medical, dental, vision, life, and disability insurance • RRSP matching • flexible spending & health savings account • paid holidays • paid time off • employee assistance program • other company benefits
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