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.

The base pay provided for this position ranges from CAD $126,400.00/ year - $158,000.00/ year depending on the geographic market and assuming a full-time schedule. Actual base pay is based on a number of factors including market location, job-related knowledge, education or training, skills, and experience.

Bonuses may also be offered as part of the total compensation package, in addition to a competitive benefits package including medical, dental, vision, life, and disability insurance; RRSP matching; flexible spending & health savings account; paid holidays; paid time off; employee assistance program; and other company benefits. 

This opening is for an existing vacancy.

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 our Ottawa office up to 1 day per week.

#LI-Hybrid

What we’re looking for

This is a highly visible, strategic, and impactful role, reporting the VP of Engineering for SurveyMonkey Core Engineering. As the Senior Director of AI, you will be a critical leader in defining the future of SurveyMonkey's products and services. You will not just manage the Machine Learning and Data Science teams, but help drive the fundamental shift in how our customers gather, analyze, and act on feedback. This requires both strong strategic thinking, and solid experience building models and deploying AI/ML systems end-to-end (from data to production). The successful candidate will make a material contribution to the company's success by providing thought leadership around how to leverage AI technology in the SurveyMonkey product in an intuitive and natural way.

What you’ll be working on

Strategic Leadership & Product Alignment

• Strategic Roadmapping: Define and execute the long-term data science strategy, ensuring alignment with SurveyMonkey’s overarching business objectives and product vision.
• Product-to-Data Science Translation: Act as the primary liaison between Product Management and the Data Science team, expertly mapping ambitious SurveyMonkey product requirements (e.g., automated thematic analysis, predictive modeling, intelligent survey generation) into clear, technically feasible data science projects.
• AI-First Transformation: Support the charge in migrating SurveyMonkey from a traditional SaaS product to an AI-first platform, embedding advanced data science and LLM capabilities deeply within the product experience.

Technical Expertise & Innovation

• LLM and NLP Integration: Drive the strategy for integrating and leveraging Large Language Models (LLMs) and advanced Natural Language Processing (NLP) techniques to enhance our text analytics, sentiment analysis, and generative features within the product.
• Familiarity with MLOps / LLMOps practices: Experience developing and deploying a Machine Learning Platform.  Experience with Agentic AI Architecture, deployment and execution. Familiarity with modern MLOps tools and platforms (e.g., AWS SageMaker, GCP Vertex AI, MLflow).
• Technical Direction: Set the technical standards for model development, deployment, monitoring, and maintenance. Ensure the team utilizes best-in-class data science models, tools, and platforms for scalable production systems.
• Ownership of model lifecycle: experimentation → deployment → monitoring → iteration
• Stay Current: Actively research, evaluate, and evangelize the latest developments in machine learning, deep learning, MLOps, and data science methodologies, ensuring the team's capabilities remain cutting-edge.

Team Management & Development

• Management and Motivation: Lead, mentor, and inspire a high-performing team of data scientists and machine learning engineers. Foster a culture of innovation, rigor, collaboration, and continuous learning.
• Recruitment and Growth: Recruit top-tier data science talent, manage performance, and define career progression paths to ensure the ongoing growth and retention of team members.

We’d love to hear from people with

• Experience: 10+ years of progressive experience in data science, including significant experience with AI/ML platforms, and at least 5 years in a Director level leadership role managing and scaling data science or machine learning teams in a commercial software environment.
• Experience building or leading AI/ML platforms: (feature stores, model serving, training pipelines) in a Cloud Environment like AWS
• Deep Technical Acumen: Extensive practical experience with and deep theoretical understanding of machine learning algorithms, statistical modeling, and experimental design (A/B testing).
• NLP and LLM Proficiency (Critical): Demonstrated experience in applying, fine-tuning, and integrating Large Language Models (LLMs) and advanced Natural Language Processing techniques into production systems, especially for tasks related to text classification, summarization, and generation.
• Product Thinking: Exceptional ability to translate ambiguous or high-level product needs into concrete, defensible data science problems and solutions.
• Communication: Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders (e.g., Executives, Product Managers, Marketing).
• Education: Master’s degree or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.

The base pay provided for this position ranges from CAD $224,000/ year - $336,000/ year depending on the geographic market and assuming a full-time schedule. Actual base pay is based on a number of factors including market location, job-related knowledge, education or training, skills, and experience.

Bonuses may also be offered as part of the total compensation package, in addition to a competitive benefits package including medical, dental, vision, life, and disability insurance; RRSP matching; flexible spending & health savings account; paid holidays; paid time off; employee assistance program; and other company benefits. 

This opening is for an existing vacancy.

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

What we’re looking for

This is a highly visible, strategic, and impactful role, reporting the VP of Engineering for SurveyMonkey Core Engineering. As the Senior Director of AI, you will be a critical leader in defining the future of SurveyMonkey's products and services. You will not just manage the Machine Learning and Data Science teams, but help drive the fundamental shift in how our customers gather, analyze, and act on feedback. This requires both strong strategic thinking, and solid experience building models and deploying AI/ML systems end-to-end (from data to production). The successful candidate will make a material contribution to the company's success by providing thought leadership around how to leverage AI technology in the SurveyMonkey product in an intuitive and natural way.

What you’ll be working on

Strategic Leadership & Product Alignment

• Strategic Roadmapping: Define and execute the long-term data science strategy, ensuring alignment with SurveyMonkey’s overarching business objectives and product vision.
• Product-to-Data Science Translation: Act as the primary liaison between Product Management and the Data Science team, expertly mapping ambitious SurveyMonkey product requirements (e.g., automated thematic analysis, predictive modeling, intelligent survey generation) into clear, technically feasible data science projects.
• AI-First Transformation: Support the charge in migrating SurveyMonkey from a traditional SaaS product to an AI-first platform, embedding advanced data science and LLM capabilities deeply within the product experience.

Technical Expertise & Innovation

• LLM and NLP Integration: Drive the strategy for integrating and leveraging Large Language Models (LLMs) and advanced Natural Language Processing (NLP) techniques to enhance our text analytics, sentiment analysis, and generative features within the product.
• Familiarity with MLOps / LLMOps practices: Experience developing and deploying a Machine Learning Platform.  Experience with Agentic AI Architecture, deployment and execution. Familiarity with modern MLOps tools and platforms (e.g., AWS SageMaker, GCP Vertex AI, MLflow).
• Technical Direction: Set the technical standards for model development, deployment, monitoring, and maintenance. Ensure the team utilizes best-in-class data science models, tools, and platforms for scalable production systems.
• Ownership of model lifecycle: experimentation → deployment → monitoring → iteration
• Stay Current: Actively research, evaluate, and evangelize the latest developments in machine learning, deep learning, MLOps, and data science methodologies, ensuring the team's capabilities remain cutting-edge.

Team Management & Development

• Management and Motivation: Lead, mentor, and inspire a high-performing team of data scientists and machine learning engineers. Foster a culture of innovation, rigor, collaboration, and continuous learning.
• Recruitment and Growth: Recruit top-tier data science talent, manage performance, and define career progression paths to ensure the ongoing growth and retention of team members.

We’d love to hear from people with

• Experience: 10+ years of progressive experience in data science, including significant experience with AI/ML platforms, and at least 5 years in a Director level leadership role managing and scaling data science or machine learning teams in a commercial software environment.
• Experience building or leading AI/ML platforms: (feature stores, model serving, training pipelines) in a Cloud Environment like AWS
• Deep Technical Acumen: Extensive practical experience with and deep theoretical understanding of machine learning algorithms, statistical modeling, and experimental design (A/B testing).
• NLP and LLM Proficiency (Critical): Demonstrated experience in applying, fine-tuning, and integrating Large Language Models (LLMs) and advanced Natural Language Processing techniques into production systems, especially for tasks related to text classification, summarization, and generation.
• Product Thinking: Exceptional ability to translate ambiguous or high-level product needs into concrete, defensible data science problems and solutions.
• Communication: Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders (e.g., Executives, Product Managers, Marketing).
• Education: Master’s degree or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.

The base pay provided for this position ranges from CAD $224,000/ year - $336,000/ year depending on the geographic market and assuming a full-time schedule. Actual base pay is based on a number of factors including market location, job-related knowledge, education or training, skills, and experience.

Bonuses may also be offered as part of the total compensation package, in addition to a competitive benefits package including medical, dental, vision, life, and disability insurance; RRSP matching; flexible spending & health savings account; paid holidays; paid time off; employee assistance program; and other company benefits. 

This opening is for an existing vacancy.

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 our Ottawa office up to 1 day per week.

#LI-Hybrid