Senior Software Engineer II
WFA Digital Insight
SurveyMonkey’s Machine Learning Platform team is looking for a senior engineer who can bridge data science and DevOps in a fully remote Canadian setting. The role centers on building and maintaining high‑throughput pipelines that power generative‑AI, NLP and real‑time classification services across the company’s survey ecosystem. You’ll own the design of AWS‑based infrastructure, embed telemetry for failure analysis, and act as an internal consultant guiding feature teams on model deployment. Beyond the code, the position includes mentoring junior engineers and shaping architectural standards for a product used by millions daily. Candidates should be comfortable with large‑scale Python data stacks, Unix environments, and the pressures of delivering reliable AI services at scale.
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, 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.
We’d love to hear from people with
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.
SurveyMonkey believes in-person collaboration is valuable for building relationships, fostering community, and enhancing our speed and execution. While this role is remote, it may require in-person participation. You will be encouraged to attend company events throughout the year. These events will take place at a designated SurveyMonkey office or location.
#LI-remote
Why SurveyMonkey? We’re glad you asked
At SurveyMonkey, curiosity powers everything we do. We’re a global company where people from all backgrounds can make an impact, build meaningful connections, and grow their careers. Our teams work in a flexible, hybrid environment with thoughtfully designed offices and programs like the CHOICE Fund to help employees thrive in work and life.
We’ve been trusted by organizations for over 25 years, and we’re just getting started. Our milestones include celebrating a quarter-century of curiosity with 25 acts of giving, opening new hubs in Costa Rica and India, crossing the threshold of 100 billion questions answered, and earning recognition as one of the Most Inspiring Workplaces across North America and Asia.
We live our company values—like championing inclusion and making it happen—by embedding them into how we hire, collaborate, and grow. They help shape everything from our culture to our business decisions. Come join us and see where your curiosity can take you.
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.
Your data
For more information on how SurveyMonkey (including its subsidiary and affiliated companies) processes your personal data as a job candidate or applicant, please see our Global Applicant and Candidate Data Privacy Notice. Please note that we may use artificial intelligence (AI) tools to support parts of the hiring process, such as sourcing candidates, reviewing applications, analyzing resumes, or summarizing interviews. These tools assist our recruitment team but do not replace human judgment.
How to Stand Out
- Highlight concrete projects where you built end‑to‑end ML pipelines on AWS; include metrics like data volume or latency if possible.
- Prepare a short code walkthrough of a Python/PySpark or PyTorch module that demonstrates clean architecture and performance considerations.
- Be ready to discuss how you instrument telemetry and handle failure analysis in production systems.
- Emphasize any mentorship experience; SurveyMonkey values engineers who lift junior teammates.
- During salary discussions, reference the typical market range for senior ML engineers in Canada and factor in remote‑work allowances.
- Watch for interview questions about trade‑offs between model accuracy and inference cost; they’ll gauge your practical engineering judgment.
- If the role mentions occasional in‑person events, confirm your ability to travel when required before accepting.
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