Senior Machine Learning Engineer - Embedded Insights

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. ABOUT THE TEAM The Embedded Insights team supports Plaid’s mission to build a world-class suite of intelligence products. We identify the best opportunities to use machine learning in Plaid products, prove out those opportunities, and collaborate with cross-functional partners to turn them into real-world production systems. ABOUT THE ROLE As a Senior Machine Learning Engineer on Embedded Insights, you will help shape Plaid’s future by building machine learning-powered products and features. You will initially support the Plaid App, working on a 0-to-1 consumer-facing product and helping establish product-market fit for a new business line. You will work closely with product managers, data scientists, engineers, customers, and other machine learning engineers to translate ambiguous opportunities into effective ML systems that create measurable customer value. In supporting the Plaid App, you will: - Build machine learning-based features for a 0-to-1 consumer-facing product. - Partner with product managers to translate ambiguous business requirements into machine learning problems and influence product strategy and roadmap decisions. - Rapidly iterate and experiment to help drive product-market fit for a new business line. - Work with Data Scientists to define success metrics and guardrails for new machine learning features. - Partner with MLEs across product areas to build effective data feedback loops. As a member of the broader Embedded Insights team, you will: - Analyze Plaid’s unique datasets to identify high-impact opportunities for machine learning and complete proofs of concept to validate them. - Embed with product teams and work closely with product and engineering partners to productionize models and deploy them in real-world, customer-facing products. - Optimize and maintain the health of existing models by developing new features, identifying effective retraining cadences, and creating metrics, alerts, and dashboards to monitor performance. - Communicate technical decisions, tradeoffs, and system behavior clearly to both technical and non-technical partners. WHAT EXCITES YOU - Shaping Plaid’s future as intelligence products become a core part of the company’s value proposition. - Working with one of the industry’s most unique datasets and helping define how Plaid can use it to create customer value. - Identifying and validating new machine learning opportunities across Plaid’s product suite. - Working across multiple product areas and developing a deep understanding of Plaid’s products and customers. - Building products that empower millions of people to achieve greater financial freedom and opportunity. - Working closely with customers to ensure products meet their needs and demonstrate meaningful impact. - Joining a high-ownership team where the greenfield opportunity is substantial. WHAT EXCITES US - 6+ years of experience in machine learning, including deploying models into real-world, customer-facing systems. - High agency and creativity, with experience identifying, defining, and proposing high-impact machine learning opportunities. - Ability to analyze large and complex financial datasets and derive actionable insights. - Experience taking machine learning systems from experimentation or proof of concept through production and ongoing improvement. - Proficiency in SQL and Python, as well as data visualization and analysis tools. - Ability to clearly communicate complex technical systems, decisions, tradeoffs, and outcomes to cross-functional partners. - Advanced degree or equivalent work experience in Statistics, Economics, Mathematics, Data Science, or a related field. Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid! Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com. Please review our Candidate Privacy Notice here https://plaid.com/legal/#candidate-privacy-notice. Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.