Senior Machine Learning Software Engineer - Remote

We are a leader in fraud prevention and AML compliance. Our platform uses device intelligence, behavior biometrics, machine learning, and AI to stop fraud before it happens. Today, over 300 banks, retailers, and fintechs worldwide use Sardine to stop identity fraud, payment fraud, account takeovers, and social engineering scams. We have raised $75M from world-class investors including Andreessen Horowitz, Visa, Experian, FIS, and Google Ventures.

We have hubs in the Bay Area, NYC, Austin, and Toronto. However, we have a remote-first work culture. #We value performance and not hours worked. We believe you shouldn't have to miss your family dinner, your kid's school play, or doctor's appointments for the sake of adhering to an arbitrary work schedule.

We are seeking a highly skilled Senior Software Engineer to lead the development of our device identification and fingerprinting systems. In this role, you will work closely with cross-functional teams to collect and process high-entropy signals from our frontend SDKs, enhance our backend systems, and improve the accuracy and reliability of our device fingerprinting methods.

Design, develop, and maintain backend services using Go (Golang) to process and analyze device data.

Data Collection Optimization : Collaborate with frontend engineers to refine data collection methodologies using JavaScript and modern browser technologies and .

Device Fingerprinting : Implement and improve algorithms for device identification using high-entropy signals and probabilistic matching techniques.

Data Analysis : Handle large datasets to extract insights and improve matching accuracy.

Browser and Technology Monitoring : Stay up-to-date with changes in browser behaviors, APIs, and security features that may impact data collection and fingerprinting methods.

Machine Learning Integration : Apply machine learning models where appropriate to enhance device recognition and handle uncertainty.

Performance Optimization : Identify bottlenecks and optimize system performance for scalability and reliability.

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

Technical Skills :

Machine Learning : Experience with machine learning algorithms and techniques. (python/notebooks/etc)

Understanding of cybersecurity principles, especially related to device identification and fraud prevention.

Experience with cloud platforms such as AWS, Google Cloud, or Azure.

DevOps Skills : Familiarity with containerization (Docker, Kubernetes) and CI/CD pipelines.

SQL Proficiency : Strong SQL skills to query, analyze, and validate data effectively, especially for large-scale datasets.

Python and Jupyter Notebooks : Experience with Python for data analysis and machine learning model development, with familiarity in using Jupyter Notebooks for prototyping and collaboration.

Additional Considerations : Knowledge of JavaScript and familiarity with modern browser APIs, especially in the context of high-entropy data collection for device fingerprinting.

Base pay range of $160,000 - $190,000 + Series B equity with tremendous upside potential + Attractive benefits

Generous compensation in cash and equity

• Remote-first Culture
• Flexible paid time off, Year-end break, Self care days off
• Health insurance, dental, and vision coverage for employees and dependents - US and Canada specific
• One-time stipend to set up a home office — desk, chair, screen, etc.
• Monthly social meet-up stipend
• 160K – $190K • Offers Equity