engineering
Posted 1 weeks agoSoftware Developer, Ops Platform and Fraud Investigations
at Robinhood
Toronto, CanadaOn-site
Responsibilities
- You will build tools that process large datasets and generate insights to support fraud investigation and decision-making
Requirements
- The Ops Platform organization develops internal platforms that replace repetitive manual processes with AI-driven systems.
- You will collaborate with data scientists and machine learning engineers to translate manual processes into automated systems.
- You will work with data scientists and machine learning engineers to implement systems that automate manual review processes
- You will design and develop AI-based applications that improve the speed and accuracy of operational tasks
- experience designing and scaling distributed systems with a focus on reliability and performance You have
- experience building and operating applications that use large language models or similar AI systems in production environments
- You understand how to structure systems that manage model behavior and ensure consistent, reliable outputs You have
- experience working with large-scale data pipelines and extracting meaningful insights from complex datasets
- Access to the best AI tools on the market and continuous AI skill-building for every employee, technical or not
- experience with catered meals, events, and comfortable workspaces.
- AI Usage Disclosure: Robinhood uses artificial intelligence (AI) tools to support parts of our recruiting process.
Benefits
- An estimated $124 trillion of assets will be inherited by younger generations in the next two decades.
- Performance driven compensation with multipliers for outsized impact, bonus programs, and equity ownership Top tier
- benefits to fuel your work, including supplemental health insurance, ancillary insurance, and mental health support programs
- Lifestyle wallet - a highly flexible employer-paid
- benefits such as wellness, childcare, learning, and more.
- Time off to recharge including company holidays, paid time off, sick time, paid volunteer time off, parental leave, and more! Exceptional office
- Monthly commuter stipend to help offset in-office commuting costs
- Vacancy Notice: This job posting represents an existing vacancy that we are actively seeking to fill.
- In addition to the base pay range listed below, this role is also eligible for bonus opportunities + equity + benefits.
- Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands.
- The expected base pay range for this role is based on the location where the work will be performed. Base Pay Range:
- Toronto, ON $136,000 — $160,000 CAD
Additional details
- If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading.
- We are building an elite team of bold thinkers and sharp problem-solvers who are wired to make an impact.
- These tools support key areas such as Fraud Operations, Account Operations, Financial Crimes Operations, and Retirement Services.
- The team works closely with product, data science, and operations partners to deliver reliable systems that improve decision-making and efficiency!
- You will work with large datasets and signals to create tooling that supports fraud investigation and other operational workflows.
- Your work will focus on improving system reliability, reducing operational effort, and increasing the speed at which new products and features can be supported across Robinhood’s offerings.
- This role is based in our Toronto, ON office, with in-person attendance expected at least 3 days per week.
- At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office
- experience is intentional, energizing, and designed to fully support high-performing teams. What you’ll do
- You will define technical direction and make architectural decisions for systems that support operational workflows across multiple product lines