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 $145M from world-class investors, including Andreessen Horowitz, Activant, Visa, Experian, FIS, and Google Ventures.
Our culture:
We have hubs in the Bay Area, NYC, Austin, and Toronto. However, we maintain a remote-first work culture. #WorkFromAnywhere
We hire talented, self-motivated individuals with extreme ownership and high growth orientation.
We value performance and not hours worked. We believe you shouldn't have to miss your family dinner, your kid's school play, friends get-together, or doctor's appointments for the sake of adhering to an arbitrary work schedule.
Location:
Remote - United States or Canada
From Home / Beach / Mountain / Cafe / Anywhere!
We are a remote-first company with a globally distributed team. You can find your productive zone and work from there.
About the Role:
We are seeking a highly skilled Machine Learning 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.
What you'll be doing:
Backend Development: 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.
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.
Security and Compliance: Ensure all systems and processes comply with relevant privacy laws and industry best practices.
Performance Optimization: Identify bottlenecks and optimize system performance for scalability and reliability.
Documentation and Mentorship: Document system designs and processes. Mentor junior team members and promote best practices within the team.
What you'll bring:
Minimum of 5 years of professional software engineering experience.
At least 3 years of experience in backend development, preferably with Go or a similar language.
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Proficiency in Go (Golang) or strong experience in another backend language with a willingness to learn Go.
Experience with data processing frameworks and handling large-scale datasets.
Experience with machine learning techniques, statistical analysis, or probabilistic modeling to improve device identification reliability and accuracy. Familiarity with Python-based data science tools and libraries (e.g., NumPy, pandas, scikit-learn) is a plus.
Familiarity with relational and non-relational databases.
Strong problem-solving abilities and analytical thinking.
Excellent communication skills, both written and verbal.
Preferred Qualifications:
Security Expertise: Understanding of cybersecurity principles, especially related to device identification and fraud prevention.
Cloud Technologies: 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.
Additional Considerations: 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 $180,000 - $220,000 + equity with tremendous upside potential + Attractive benefits
The compensation offered for this role will depend on various factors, including the candidate's location, qualifications, work history, and interview performance, and may differ from the stated range.
Benefits we offer:
Generous compensation in cash and equity
Early exercise for all options, including pre-vested
Work from anywhere: 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
4% matching in 401k / RRSP - US and Canada specific
MacBook Pro delivered to your door
One-time stipend to set up a home office — desk, chair, screen, etc.
Monthly meal stipend
Monthly social meet-up stipend
Annual health and wellness stipend
Annual Learning stipend
Unlimited access to an expert financial advisory
Join a fast-growing company with world-class professionals from around the world. If you are seeking a meaningful career, you found the right place, and we would love to hear from you.
