Senior Machine Learning Engineer

October 31

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Rocket Money (formerly Truebill)

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Description

• Build new, machine learning powered user-facing features and experiences in deep collaboration with engineering, product, and design teams. Use your expertise in ML system and model design to delight our customers with new user experiences. Work with engineering teams to build software to deliver new experiences to Rocket Money’s customers. • Optimize to continuous product feedback loops - you understand that machine learning is the practice of a continuous lifecycle of measurement, analysis, modeling, and hypothesis testing. You understand how to build, test, and deliver user-facing machine learning products in an incremental way. • Help develop the next version of Autopilot and Budgets. Ensure members have money in the right place at the right time for their near and long term goals. Warn them when they do not. • Uncover and exploit relationships between customers’ subscriptions, purchase, and transaction data as you build personalized product experiences and power ever more accurate customer segmentation, propensity, and affiliate targeting models. • Design and conduct experiments to estimate the impact of new ml driven products, customer messaging, and marketing. You know how to use experimentation to build the strategic case for more tailored ML product experiences. • Build anomaly detection systems, ensuring that our transaction categorization systems produce accurate data for our users and tracking when they don’t. • Work within cross-functional teams to build new products and services, especially with engineering. • Become a subject matter expert in your area of specialty - making key decisions on both implementation and scope while balancing technical and business goals. • Become an expert on our members. Understand their needs and financial goals. Work with product to define strategy and engineering teams to create software and build features that help our members build better financial lives. • Design ML system and model architecture to aid product delivery, both internal and external. • Be a steward of good instrumentation and experimental design - designing systems to measure the impact of ML powered products in a way that is measurable, testable, repeatable, and robust. • Extend internal tooling that improves the data science and ML product implementation - help accelerate the work of others on engineering and data teams. • Participate in code reviews, contribute to product and technical design, and maintain a high degree of quality in our production data.

Requirements

• You are a team player - collaboration and communication are a first instinct and key tool for getting stuff done. You continually seek feedback on your work and err on the side of over communicating. • You care about products, not publications. Solving user problems is of key importance for you, not necessarily finding esoteric problems. We love recovering academics that aren’t looking in the rearview. • You can collaborate with stakeholders to define tasks, defining cross-functional work independently to achieve strategic goals • You know how to deliver products incrementally - doing the simple thing first, finding and measuring signal, and iterating to build better user experiences. • Excellent writing, presentation, and communication skills. Documenting, soliciting feedback, and securing alignment among collaborators is second nature. • You have strong software engineering skills. You can contribute up and down the application stack to deliver data products to users. Evidenced experience working with engineering teams to build software is an absolute must. • You have a lot of tools in your methodological tool belt and are prolific in testing multiple approaches. • You have 3+ years of professional experience working in a data science or machine learning engineering capacity. You know your way around databases, data warehouses, models, and how to engineer backend machine learning and data science systems. Bonus points if you have experience integrating data products into application front ends. You are equally adept at hacking together proof of concepts and working within engineering teams to build scalable, durable systems. • You care just as much about why you're solving a problem as the solution. You always want a deep understanding of context and business impact. You are an ML engineer first but an expert data scientist and analyst when necessary. • You want to continue to grow and learn. You are excited by hard problems and big challenges. • Experience in fintech, banking, or finance is a plus.

Benefits

• Health, Dental & Vision Plans • Competitive Pay • 401k Matching • Unlimited PTO • Lunch daily (in-office only) • Snacks & Coffee (in-office only) • Commuter benefits (in-office only)