Senior Machine Learning Engineer (MLE)
Quandri
Full-time
On-site
Vancouver, Canada
$160,000 - $190,000 USD yearly
AI and Machine Learning
Who we are
At Quandri, our mission is to unlock the world’s insurance data so brokerages and agencies can deliver the best possible service to their clients. Our Renewal Intelligence Platform is designed to help agencies save time, increase profitability, and drive better outcomes for their staff, clients, and business.
What we do
Running a profitable personal lines book of business is harder than ever for insurance brokerages and agencies. Rising costs, market shifts, and staffing challenges make it tough to scale while delivering exceptional client service. Trusted by 100+ insurance agencies across North America, Quandri is transforming the policy renewal process with AI-driven automation, delivering data-driven insights, and enabling proactive workflows.
Because of the high volume, high velocity nature of personal lines, today’s renewal process is often reactive — with brokers and agents focusing on clients who request help rather than adopting a proactive, data-driven approach. Quandri changes that. Our platform automates routine tasks, highlights at-risk accounts, and arms advisors with timely, data-driven recommendations. The result? Higher retention, more upsell and cross-sell opportunities, reduced E&O risk, and a better experience for both staff and clients.
Why join us?
At Quandri, you’ll make a real impact alongside a team that’s as innovative and diverse as the industry we serve. Our culture is built around curiosity, collaboration, and continuous improvement. We’re a hybrid company with ¾ of our team in Vancouver and the rest distributed. Our Vancouver office is in Olympic Village, where we collaborate in person three days a week. We believe in flexibility, and we also know that great ideas come from working together.
We’re backed by leading US and Canadian investors and are scaling quickly. We saw 3x ARR growth last year and plan to continue growing both revenue and our team. Named one of LinkedIn’s Top Canadian Startups in 2024 & 2025, we’ve already made a meaningful impact on the insurance industry. We’ve also been named to Deloitte’s Fast 50, highlighted on CB Insights’ Insurtech 50 and Fintech 100 lists, and featured amongst the Globe and Mail’s Top Growing Companies in Canada.
Now, we want you to be part of our journey.
About the Role:
- As a Senior MLE at Quandri, you will help drive the evolution of our continuous learning system behind our AI and analytics work. This role will design and implement real-time learning systems that continuously evolve Quandri's insurance intelligence from every bot interaction, document processed, and customer feedback, establishing the core infrastructure for our learning flywheel. You will build feedback loop architectures and models that capture and integrate signals from broker activities and customer interactions that improve model and product accuracy, reliability and capabilities, enabling Quandri to deliver increasingly intelligent insights that surpass any individual broker's capabilities.
What you’ll do:
- Conduct advanced statistical analysis, explore complex datasets to uncover business opportunities, perform market research through data
- Partner with Product, Engineering, Sales, Marketing, and Leadership stakeholders to translate business questions into analytical frameworks and data-driven solutions
- Build predictive models, forecasting, impact analysis, statistical models and the systems around them, to support business decision-making
- Identify new analytical opportunities, research emerging methodologies, leverage the AI tools, and drive data science best practices
- End-to-end ownership: Can take models from research to production and maintain them
- Work closely with our team of Data Engineers, ML Engineers, AI Engineers, ML Ops, Software Engineers and Data Scientists to integrate data insights, engineering best practices and tech review to deliver production systems and analysis
- Own the ML model lifecycle for your core products (Renewals, Requoting, Connect)
- Build the continuous learning infrastructure that feeds back into model and product improvement
The right person for this role will have:
- Advanced degree (MS/PhD) in Statistics, the Sciences, Mathematics, Computer Science or related quantitative field
- 4-7 years of experience in ML engineering or data engineering roles with proven track record of driving business impact through analytics
- Advanced proficiency in Python/R, and SQL Expertise in building feedback loop integration systems that take feedback from from engineering services, product activities, and customer interactions
- Strong foundation in reinforcement learning, self-supervised learning or human in the loop learning
- Experience translating business problems into analytical questions and communicating technical findings to non-technical stakeholders
- Proven ability to communicate complex ideas clearly, collaborate across teams, lead projects from concept to delivery, and inspire others through strong leadership
- Experience in agile, fast moving, and high impact business environments preferred
- Customers at the core. We put the customer at the center of all we do. At a basic level, we believe business success comes down to talking to customers and building something they want. We don’t listen to customers and just take what they say blindly, but we think critically about it and build what they need. Customers are the core of everything we do, and our business exists to serve them. We prioritize their needs over all else within the company.
- Move with urgency. There are times when we need to move slowly and deliberately, but we default to acting fast and with urgency. We slow down when necessary, but this should be a deliberate choice. Businesses become more lethargic as they grow, this principle is designed to fight this fact.
- Be curious. We understand the world by being curious and asking why. We aren’t satisfied with surface level understanding, and seek a deeper understanding of why things are the way they are. Don’t take someone’s word for it or the answer “because that’s how we do it.” Understand why and dig deep.
- Excellence in execution. We know that what separates good from great is a high level of execution. We commit ourselves to excellence in everything that we do, from delivering an amazing product to writing a great email.
- Act like an owner. We’re all owners of the business and act like it. We follow through on commitments, own our results and think long-term.
- Fight for simplicity. The law of increasing functional information states that systems evolve to become more complex over time. At Quandri, we believe there is sophistication in simplicity; as such, we intentionally fight for streamlined solutions and are committed to the uncomplicated.
Our guiding principles:
$160,000 - $190,000 a year
Compensation and Benefits:
The range for base pay is $160,000-$190,000 which is dependent on level of experience, performance and choice of stock option compensation
Employee stock options based on experience level
Comprehensive health benefits, including $500 Lifestyle Spending Account
Four weeks of paid vacation per year
Work anywhere in the world for 60 calendar days of the year
Parental leave top-ups: 6 months for birthing parents, 8 weeks for non-birthing parents (up to $100,000 annual salary)
Quandri is dedicated to fostering a diverse and inclusive workplace. As an equal opportunity employer, Quandri adheres to Canadian labour laws and does not engage in discrimination based on race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or any other status protected under Canadian law.
Don’t let imposter syndrome stop you from applying. Great people sometimes don’t have the “right” experience. If you think that you’ll be amazing at this role then we encourage you to apply.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.