Senior Software Engineer

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SurveyMonkey

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1999

☁️ SaaS

🤝 B2B

⚡ Productivity

💰 $250M Private Equity Round on 2014-12

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.

📋 Description

• 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.

🎯 Requirements

• 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.

🏖️ Benefits

• Flexible, hybrid environment with thoughtfully designed offices • Professional development opportunities