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Home›Jobs›Block›Staff Machine Learning Engineer, Risk Signals & Controls
Block

About Block

Empowering economic freedom through innovative financial solutions

🏢 Tech👥 10K-50K📅 Founded 2009📍 San Francisco, California, United States

Key Highlights

  • Public company (NYSE: SQ) with a market cap over $40B
  • Over 50 million monthly active users across its platforms
  • Headquartered in San Francisco, California
  • Offers products like Square, Cash App, and TIDAL

Block, headquartered in San Francisco, California, is a financial technology company that provides a suite of products including Square, Cash App, and TIDAL. With over 50 million monthly active users, Block is focused on economic empowerment through accessible financial services. The company went pu...

🎁 Benefits

Block offers competitive salaries, equity options, generous PTO policies, and comprehensive health benefits. Employees enjoy a flexible remote work po...

🌟 Culture

Block fosters a culture of inclusivity and innovation, encouraging diverse perspectives to drive solutions. The company emphasizes collaboration acros...

🌐 Website𝕏 TwitterAll 290 jobs →
Block

Staff Machine Learning Engineer, Risk Signals & Controls

Block • Bay Area, CA, United States of America

Posted 3w ago🏛️ On-SiteStaffMachine learning engineer📍 Bay area
Apply Now →

Skills & Technologies

PythonAWSDockerKubernetesTensorFlowPyTorchSQLData engineeringMachine learningData pipelines

Overview

Block is hiring a Staff Machine Learning Engineer for their Risk Signals & Controls team to design and maintain data pipelines and ML models for fraud detection. You'll work with technologies like Python, AWS, and TensorFlow. This role requires 12+ years of experience in software development.

Job Description

Who you are

With over 12 years of experience in software development, you have demonstrated technical initiative and leadership in machine learning projects. You possess a deep understanding of data engineering and machine learning principles, and you are skilled in building efficient data pipelines and ML models. Your experience includes collaborating with cross-functional teams to optimize signal quality and enhance model effectiveness. You are comfortable working with large datasets and have a strong grasp of data validation and monitoring practices. You thrive in a collaborative environment and are eager to explore new directions in machine learning.

Desirable

Experience with fraud detection systems or risk management is a plus. Familiarity with real-time data processing and transaction monitoring will set you apart. You are also encouraged to bring innovative ideas to the table, pushing the boundaries of what is possible in the field of machine learning.

What you'll do

In this role, you will design, build, and maintain data pipelines that ingest third-party and Block data to enhance the feature store and modeling capabilities. You will create elegant ML pipelines and services, prototype new approaches, and productionize solutions at scale. Your responsibilities will include building tooling to maintain features and models, ensuring efficiencies in fraud detection. You will work closely with ML Modelers to identify and integrate new data sources, heuristics, and models, solving challenging technical problems at scale. You will apply ML and engineering best practices to shape how Block develops, tests, and maintains ML-platform solutions. Additionally, you will ensure data quality and completeness through automated validation, monitoring, and alerting, taking ownership of your solutions from design through to operation.

What we offer

At Block, you will be part of a mission-driven team that is transforming the way customers manage their spending. You will have the opportunity to work on innovative projects that have a real impact on the financial system. We offer a collaborative work environment where your contributions are valued, and you will have the chance to grow your skills and advance your career. We encourage you to apply even if your experience doesn't match every requirement, as we believe diverse teams build better products.

Interested in this role?

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