Senior Machine Learning Engineer (MLE) at Quandri | Torre

Senior Machine Learning Engineer (MLE)

You’ll engineer AI’s continuous learning and shape insurance intelligence.
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Full-time

Legal agreement: Employment

Compensation
USD160k - 190k/year
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Hybrid (Vancouver, BC, Canada)
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Posted 6 months ago

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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 dataPartner with Product, Engineering, Sales, Marketing, and Leadership stakeholders to translate business questions into analytical frameworks and data-driven solutionsBuild predictive models, forecasting, impact analysis, statistical models and the systems around them, to support business decision-makingIdentify new analytical opportunities, research emerging methodologies, leverage the AI tools, and drive data science best practicesEnd-to-end ownership: Can take models from research to production and maintain themWork 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 analysisOwn the ML model lifecycle for your core products (Renewals, Requoting, Connect)Build the continuous learning infrastructure that feeds back into model and product improvementThe right person for this role will have:Advanced degree (MS/PhD) in Statistics, the Sciences, Mathematics, Computer Science or related quantitative field4-7 years of experience in ML engineering or data engineering roles with proven track record of driving business impact through analyticsAdvanced proficiency in Python/R, and SQL. Expertise in building feedback loop integration systems that take feedback from engineering services, product activities, and customer interactionsStrong foundation in reinforcement learning, self-supervised learning or human in the loop learningExperience translating business problems into analytical questions and communicating technical findings to non-technical stakeholdersProven ability to communicate complex ideas clearly, collaborate across teams, lead projects from concept to delivery, and inspire others through strong leadershipExperience in agile, fast moving, and high impact business environments preferredOur guiding principles: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.Salary Range$160,000 - $190,000 a yearCompensation 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 compensationEmployee stock options based on experience levelComprehensive health benefits, including $500 Lifestyle Spending AccountFour weeks of paid vacation per yearWork anywhere in the world for 60 calendar days of the yearParental leave top-ups: 6 months for birthing parents, 8 weeks for non-birthing parents (up to $100,000 annual salary)ClosingQuandri 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.AI disclaimerWe 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.
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