• Work directly with CV researchers to understand their goals, review their code, and engineer it for reliability and performance at scale. • Profile and optimize performance-sensitive code across both training and real-time inference. • Identify patterns across research efforts and propose standardized, composable abstractions. • Collaborate with MLOps and backend engineers to translate recurring research pain points into platform investments through design documents and architecture proposals. • Guide researchers toward production-oriented engineering practices regarding testability, modularity, and performance profiling.

The Role The Risk Signals and Controls team's mission is to power Block's risk decisions with trusted signals and lean, effective models built on evolving data. We do that by building efficient tools and workflows to accelerate fraud detection and model effectiveness evaluating thousands of transactions per second in real time. We closely collaborate with ML Modellers and Software Engineers from across Block to optimize the signal lifecycle to improve signal quality, reduce noise, and accelerate time-to-insight. We're also excited to explore new directions with the team to continue pushing the boundaries of what's possible. You Will Design, build, and maintain data pipelines to ingest third parties and Block data to enhance our feature store and modeling capabilities. Design elegant ML pipelines and services, prototype new approaches, and productionize solutions at scale. Build tooling to help maintain our features and models, gaining efficiencies in fraud detection. Work hand-in-hand with ML Modelers to identify and integrate new data sources, heuristics and models. Solve challenging technical problems at scale, collaborating with colleagues located across the globe Apply ML and engineering best practices to shape how Block develops, tests, and maintains ML-platform solutions. Ensure data quality and completeness through automated validation, monitoring, and alerting. Own your solutions from design through to operation: we all share the pager! You Have 12+ years of experience in software development and demonstrated technical initiative and leadership on previous machine learning projects. A proven ability to shape how teams effectively adopt and evolve AI practices; driving adoption of AI-first workflows by coaching leaders, identifying scalable use cases, and embedding quality and accountability in team norms. Work autonomously in a fast paced, ambiguous and unpredictable environment Natural curiosity & eagerness to learn Show the ability to take initiative, lead, and drive creative solutions in cross-team contexts. A strong interest in owning your solutions, maintaining and fixing them as necessary Communicate via clear and concise writing to facilitate asynchronous collaboration across multiple time zones Reason about complex, distributed systems at high scale Proficiency in machine learning techniques, experimental design and data engineering Strong programming skills in languages such as Kotlin, Python, TensorFlow, or PyTorch Technologies We Use and Teach We value general engineering skill and versatility over existing domain knowledge, but here's a sample of what we currently use: Python, Java and Kotlin HTTP, JSON, gRPC, Protocol Buffers AWS, Databricks, and Kubernetes MySQL, DynamoDB, Kafka, Spark Prefect, Airflow We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is a proud equal opportunity employer. We work hard to evaluate all employees and job applicants consistently, based solely on the core competencies required of the role at hand, and without regard to any legally protected class. We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we're doing to build an inclusive workplace? Check out our Inclusion & Diversity page Full-time employee benefits include the following: Healthcare coverage (Medical, Vision and Dental insurance) Health Savings Account and Flexible Spending Account Retirement Plans including company match Employee Stock Purchase Program Wellness programs, including access to mental health, 1:1 financial planners, and a monthly wellness allowance Paid parental and caregiving leave Paid time off (including 12 paid holidays) Paid sick leave (1 hour per 26 hours worked (max 80 hours per calendar year to the extent legally permissible) for non-exempt employees and covered by our Flexible Time Off policy for exempt employees) Learning and Development resources Paid Life insurance, AD&D, and disability benefits These benefits are further detailed in Block's policies. This role is also eligible to participate in Block's equity plan subject to the terms of the applicable plans and policies, and may be eligible for a sign-on bonus. Sales roles may be eligible to participate in a commission plan subject to the terms of the applicable plans and policies. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans. Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate's starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.

The Role As a Staff Machine Learning Engineer in Fraud and Abuse ML Engineering, you will play a central role in designing, building, and evolving the machine learning systems that safeguard Block's ecosystem from fraud, abuse, and other malicious activity. You will architect and lead the development of high-scale, real-time ML systems that power our fraud decisioning across the Block network, protecting millions of customers and merchants while maintaining seamless user experiences. You Will Build and maintain real-time and batch data pipelines/APIs to support ML model inference at scale. Design elegant ML pipelines and services, prototype new approaches, and productionize solutions at scale. Collaborate with product and engineering teams to define data models and schemas for consistent and structured data flow. Integrate and enrich diverse internal and third-party data sources to enhance our feature store and modeling capabilities. Ensure data quality and completeness through automated validation, monitoring, and alerting. Develop new triggers and event hooks that support enhanced risk evaluations and detections. Participate in SEV management by rapidly integrating new data, deploying new features, and implementing stopgap controls to mitigate risk. Apply ML and engineering best practices to shape how Block develops, tests, and maintains ML-platform solutions. Support the integration of risk decisions and scores into downstream systems, ensuring they are consumed and acted upon correctly. You Have 12+ years of experience in software development and demonstrated technical initiative and leadership on previous machine learning projects. A proven ability to shape how teams effectively adopt and evolve AI practices; driving adoption of AI-first workflows by coaching leaders, identifying scalable use cases, and embedding quality and accountability in team norms. Experience leading experimentation cycles and building a shared understanding of how AI drives business outcomes. Curiosity and a passion for Block's mission of economic empowerment. Experience helping your teammates grow through mentorship and providing constructive feedback. A desire to be hands-on and help invent the future of AI. The ability to work autonomously in the rapidly evolving world of ML. Technologies We Use and Teach Python, Java and Kotlin Tensorflow and PyTorch AWS, Databricks and Kubernetes MySQL, DynamoDB, Kafka, Spark We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is a proud equal opportunity employer. We work hard to evaluate all employees and job applicants consistently, based solely on the core competencies required of the role at hand, and without regard to any legally protected class. We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we're doing to build an inclusive workplace? Check out our Inclusion & Diversity page Full-time employee benefits include the following: Healthcare coverage (Medical, Vision and Dental insurance) Health Savings Account and Flexible Spending Account Retirement Plans including company match Employee Stock Purchase Program Wellness programs, including access to mental health, 1:1 financial planners, and a monthly wellness allowance Paid parental and caregiving leave Paid time off (including 12 paid holidays) Paid sick leave (1 hour per 26 hours worked (max 80 hours per calendar year to the extent legally permissible) for non-exempt employees and covered by our Flexible Time Off policy for exempt employees) Learning and Development resources Paid Life insurance, AD&D, and disability benefits These benefits are further detailed in Block's policies. This role is also eligible to participate in Block's equity plan subject to the terms of the applicable plans and policies, and may be eligible for a sign-on bonus. Sales roles may be eligible to participate in a commission plan subject to the terms of the applicable plans and policies. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans. Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate's starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.

Block builds technology to increase access to the global economy. Across our ecosystem, including Square and Cash App, we create tools that help businesses run and grow, and individuals move, manage, and grow their money with confidence. Square empowers sellers of all sizes with integrated, omnichannel tools to accept payments, manage operations, access financial services, and reach customers across online and in-person channels. Cash App complements this by providing a fast, accessible financial platform for millions of people to send, spend, save, invest, and borrow, helping redefine how individuals interact with money.Operating at massive scale across both ecosystems means trust and safety are foundational. Our teams build systems that protect real people and businesses, safeguard financial activity, and ensure our products remain reliable, secure, and easy to use. Block is a global, distributed company with a culture rooted in ownership, creativity, and impact. Whether supporting sellers on Square or customers on Cash App, we're united by a shared mission: to make the global economy more accessible and inclusive. The Role We're hiring Senior Machine Learning Engineers to join Block's Risk Machine Learning organization, where teams apply ML at massive scale to detect, prevent, and reduce fraud and abuse across Cash App and Square. This opening supports multiple senior-level roles, with team placement determined through a collaborative matching process based on your experience, interests, and current business needs. Today, we're growing teams focused on chargeback and fraud prevention as well as trust and safety initiatives supporting Cash App Families and teen banking. Across teams, your work will directly protect our ecosystem, reduce financial loss, and enable safe, seamless financial experiences for millions of customers, sellers, and families. Team Focus Areas Depending on your background and interests, you may join a team focused on one of the following areas: Fraud & Chargeback Risk Build machine learning models and systems that detect fraudulent transactions, reduce chargebacks, and protect the integrity of payments across Cash App and Square. Trust, Safety & Families Develop machine learning systems that enable safe and trustworthy financial experiences for teens and families by detecting risky or abusive behavior, strengthening account integrity, and supporting long-term trust in Cash App. Both teams value first-principles thinking, rapid iteration, and shipping production ML solutions with real-world impact. You Will Partner with product, engineering, data science, policy, and operations to design and productionize ML-driven risk solutions at scale Own end-to-end machine learning systems, from problem definition and modeling to deployment, monitoring, and iteration Lead technical decision-making within your workstreams and influence ML strategy and planning Build tooling and processes that improve the speed, reliability, and impact of the ML development lifecycle Apply state-of-the-art modeling techniques and third-party data sources to improve detection and decision-making Investigate emerging fraud, abuse, and risk patterns to proactively inform product safeguards and policy Collaborate closely with ML platform and engineering teams to ensure models operate reliably in real time and at scale You Have 2+ years of industry experience in machine learning, applied AI, or related fields Bachelor's degree in a quantitative field (Computer Science, Engineering, Statistics, Physics, Applied Math); Master's or PhD preferred Proven experience independently designing, deploying, and maintaining ML solutions in production Strong familiarity with techniques such as tree-based models, deep learning, transfer learning, or reinforcement learning Experience influencing technical direction and collaborating with cross-functional partners at scale Strong communication skills, sound judgment, and an ownership mindset Curiosity and alignment with Block's mission of economic empowerment Technologies We Use and Teach Python (NumPy, Pandas, scikit-learn, XGBoost, PyTorch, TensorFlow/Keras) PySpark, MLflow, workflow orchestration tools (Airflow, Prefect) GCP (Vertex AI), AWS Snowflake, MySQL, Tableau, Mode Containerization, CI/CD, and production ML best practices Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate's starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.