Senior Software Engineer / Machine Learning Engineer (Device Identification)
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Who we are
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.
Our culture
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We have hubs in the Bay Area, NYC, Austin, and Toronto. However, we have a remote‑first work culture.
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We hire talented, self‑motivated people and get out of their way.
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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.
Job Summary
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.
Key Responsibilities
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Backend Development : Design, develop, and maintain backend services using Go (Golang) to process and analyze device data.
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Data Collection Optimization : Collaborate with frontend engineers to refine data collection methodologies using JavaScript and modern browser technologies.
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Device Fingerprinting : Implement and improve algorithms for device identification using high‑entropy signals and probabilistic matching techniques.
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Data Analysis : Handle large datasets to extract insights and improve matching accuracy.
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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.
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Machine Learning Integration : Apply machine learning models where appropriate to enhance device recognition and handle uncertainty.
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Security and Compliance : Ensure all systems and processes comply with relevant privacy laws and industry best practices.
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Performance Optimization : Identify bottlenecks and optimize system performance for scalability and reliability.
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Documentation and Mentorship : Document system designs and processes. Mentor junior team members and promote best practices within the team.
Qualifications
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Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Preferred Qualifications
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Experience with machine learning algorithms and techniques. (Python/notebooks/etc)
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Understanding of cybersecurity principles, especially related to device identification and fraud prevention.
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Experience with cloud platforms such as AWS, Google Cloud, or Azure.
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Familiarity with containerization (Docker, Kubernetes) and CI/CD pipelines.
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Strong SQL skills to query, analyze, and validate data effectively for large‑scale datasets.
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Experience with Python for data analysis and machine learning model development; familiarity with Jupyter Notebooks for prototyping and collaboration.
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Knowledge of JavaScript and familiarity with modern browser APIs, especially in the context of high‑entropy data collection for device fingerprinting.
Compensation
Base pay range of $160,000 – $190,000 + Series B equity with tremendous upside potential + Attractive benefits.
Benefits
we offer
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Generous compensation in cash and equity.
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Early exercise for all options, including pre‑vested.
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Work from anywhere: Remote‑first culture.
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Flexible paid time off, year‑end break, self‑care days off.
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Health insurance, dental, and vision coverage for employees and dependents (US and Canada specific).
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4% matching in 401k / RRSP (US and Canada specific).
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MacBook Pro delivered to your door.
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One‑time stipend to set up a home office — desk, chair, screen, etc.
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Monthly meal stipend.
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Monthly social meet‑up stipend.
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Annual health and wellness stipend.
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Annual learning stipend.
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Unlimited access to an expert financial advisory.
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