Signifyd

About Signifyd

Empowering eCommerce with fraud protection solutions

🏢 Tech👥 501-1000 employees📅 Founded 2011📍 Downtown San Jose, San Jose, CA💰 $411m4.8
FintechB2BBig dataSaaSCyber SecurityFraud

Key Highlights

  • Headquartered in downtown San Jose, CA
  • $411 million raised in Series D funding
  • Serves major clients like Samsung, Lenovo, and Walmart
  • Employs between 501-1000 people

Signifyd is a leading provider of fraud protection and cybersecurity solutions for eCommerce, headquartered in downtown San Jose, CA. The company offers an end-to-end security platform that helps brands like Samsung, Lenovo, and Walmart prevent fraud and reduce chargebacks. With $411 million raised ...

🎁 Benefits

Signifyd offers equity options, a 4-day workweek, generous PTO, and a remote work policy to support work-life balance....

🌟 Culture

Signifyd fosters a culture focused on innovation and efficiency, utilizing a data-driven approach to combat fraud while empowering employees to make i...

Overview

Signifyd is hiring a Senior Machine Learning Engineer to build and maintain production ML models and frameworks for fraud detection. You'll work with Python, TensorFlow, and Keras to enhance customer experiences. This role requires strong expertise in machine learning and statistical analysis.

Job Description

Who you are

You have 5+ years of experience in machine learning engineering, with a strong background in building and deploying production ML models. Your expertise in Python is complemented by your familiarity with frameworks like TensorFlow and Keras, allowing you to create robust models that drive business outcomes. You understand the intricacies of statistical analysis and can apply these principles to improve model performance and accuracy. You are passionate about combating fraud and are motivated by the challenge of staying ahead of sophisticated adversaries. Your collaborative spirit enables you to work effectively with cross-functional teams, including Platform Engineering, to integrate advanced modeling methods into existing systems. You are committed to continuous learning and are eager to explore new techniques in adversarial machine learning.

Desirable

Experience with cloud platforms such as AWS or GCP is a plus, as is familiarity with data engineering practices. You may also have experience in feature engineering and offline experimentation frameworks, which will enhance your contributions to the team. A background in e-commerce or fraud detection systems would be beneficial, as it aligns with Signifyd's mission to empower online retailers.

What you'll do

As a Senior Machine Learning Engineer at Signifyd, you will be responsible for building and maintaining the core fraud detection models that are crucial to our operations. You will collaborate closely with the ML team to develop and monitor production ML models, ensuring they perform optimally in real-time environments. Your role will involve designing and implementing offline experimentation frameworks that allow for rigorous testing and validation of new modeling approaches. You will contribute to the development of novel modeling methods and advanced feature engineering techniques, leveraging your statistical expertise to enhance model accuracy and reliability. You will also engage in regular communication with Platform Engineering teams to ensure seamless integration of ML solutions into our existing infrastructure. Your work will directly impact the customer experience by enabling merchants to confidently process transactions while minimizing fraud risk.

What we offer

At Signifyd, we foster a culture of tenacity, curiosity, and collaboration. You will be part of a team that values your contributions and encourages you to grow professionally. We offer competitive compensation, including an annual performance bonus of up to 10% of your base salary. Our inclusive work environment ensures that all employees feel valued and supported, with reasonable accommodations available for those who need them. Join us in our mission to empower fearless commerce and make a meaningful impact in the world of online retail.

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