SurveyMonkey is the world’s most popular platform for surveys and forms, built for business—loved by users. We combine powerful capabilities with intuitive design, effectively serving every use case, from customer experience to employee engagement, market research to payment and registration forms. With built-in research expertise and AI-assisted technology, it’s like having a team of expert researchers right at your fingertips.
Trusted by millions—from startups to Fortune 500 companies—SurveyMonkey helps teams gather insights and information that inspire better decisions, create experiences people love, and drive business growth. Discover how at surveymonkey.com.
What we’re looking for
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. The goal is to build applications and tools that enable the scalability of ML along all points of the lifecycle of an AI project, from feature discovery to model training, from model deployment to post-production monitoring and evaluation.
What you’ll be working on
- As an ML Engineer, you will design and implement secure, scalable, and high-performance pipelines managing the end-to-end lifecycle of ML models.
- Collaborating closely with SurveyMonkey's application engineers, you'll integrate, test, and monitor ML model services across our product portfolio.
- The MLP team's focus includes supporting services for ML models and extending architecture to integrate with other SurveyMonkey microservices.
- We need your help as we continue to evolve our ML platform here at SurveyMonkey. We help our customers make great decisions based on the tools we create on top of the millions of survey responses we receive daily.
- We use applied machine learning techniques that include generative AI, natural language processing, classification, spam detection, personalization/ranking, etc. at a significant scale and generally in real-time.
We’d love to hear from people with
- 2+ years of ML engineering experience using Python 3 in backend development and AWS for model deployment/serving.
- Basic data engineering experience using tools such as S3 or SQL to extract features for model-building.
- Basic model-building experience using tools such as SageMaker.
- Experience with Unix/Linux operating systems (Ubuntu preferred).
- Comfortable with machine learning techniques including LLMs.
- Experience deploying end-to-end solutions with creative problem-solving skills to handle a high volume of throughput.
SurveyMonkey believes in-person collaboration is valuable for building relationships, fostering community, and enhancing our speed and execution in problem-solving and decision-making. As such, you will be required to work from a SurveyMonkey office up to 1 day every other week.
#LI - Hybrid
Why SurveyMonkey? We’re glad you asked
SurveyMonkey is a place where the curious come to grow. We’re building an inclusive workplace where people of every background can excel no matter their time zone. At SurveyMonkey, we weave employee feedback and our core values into everything we do to create forward-looking benefits policies, employee programs, and an award-winning culture, including our annual holiday refresh, our annual week of service, learning and development opportunities like Curiosity Week, and our C.H.O.I.C.E Fund.
Our commitment to an inclusive workplace
SurveyMonkey is an equal opportunity employer committed to providing a workplace free from harassment and discrimination. We celebrate the unique differences of our employees because that is what drives curiosity, innovation, and the success of our business. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, pregnancy, parental status, genetic information, political affiliation, or any other status protected by the laws or regulations in the locations where we operate. Accommodations are available for applicants with disabilities.
