SurveyMonkey
Technology
SeniorSoftwareEngineerII
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Software Engineer II at SurveyMonkey. Skills: Machine Learning, MLOps, Cloud Infrastructure, Data Engineering. Design and implement secure pipelines. Implement highly scalable pipelines”
What You'll Achieve.
Deliver results meeting dynamic needs
Industry & Context.
Failure mode analysis
In-person participation may be required, Attend company events
What They're Looking For.
Must Have
8+ years professional ML development experience, Designing and implementing ML infrastructure in AWS, Mastery of ML concepts, Deep understanding of Large Language Models, Deep understanding of NLP, Expert-level Python skills, Experience with high-scale data processing, Comfortable with Unix/Linux systems, Experienced in deploying end-to-end solutions for real-time applications, Bachelor's Degree in Computer Science, Bachelor's Degree in Data Science, Bachelor's Degree in Software Engineering, Bachelor's Degree in Mathematics, Bachelor's Degree in Statistics, Bachelor's Degree in a related quantitative field
Nice to Have
Experience with PySpark
What You'll Do.
Design and implement secure pipelines
Implement highly scalable pipelines
Implement high-performance pipelines
Govern end-to-end ML model lifecycle
Build robust ML systems
Maintain robust ML systems
Support efficient ML operations
Design ML cloud infrastructure
Ensure platform reuse
Ensure platform scalability
Ensure high-volume throughput
Integrate ML model services
Test ML model services
Monitor ML model services
Act as consultant to internal teams
Educate internal teams
Influence decisions regarding ML tooling
Influence decisions regarding ML infrastructure
Incorporate telemetry into platform
Analyze complex failure modes
Ensure real-time reliability
Serve as technical leader
Mentor junior engineers
Champion high standards in coding
Champion high standards in documentation
Champion high standards in architectural best practices
How You'll Work.
Team & Collaboration
Cross-functional teams; Application engineers; Internal feature teams
Communication Scope
Educating teams; Influencing decisions
Full Job Description
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-powered technology, it’s like having a team of expert researchers 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 team (MLP) is seeking a Senior Software Engineer II to design and implement the secure, highly scalable, and high-performance pipelines that govern the end-to-end lifecycle of ML models. You will work at the intersection of Data Science and DevOps, building the "connective tissue" that empowers our product portfolio to leverage technologies like Generative AI, Natural Language Processing (NLP), and real-time classification. We are looking for a subject matter expert who will drive innovation and deliver results that meet the dynamic needs of a high-growth AI environment. You will report to the Senior Engineering Manager on the MLP Solutions team. What you’ll be working on 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, ensur
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