Senior Software Engineer / Machine Learning Engineer (Device Identification)
US / Canada - Remote
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:
We have hubs in the Bay Area, NYC, Austin, and Toronto. However, we have a remote-first work culture. #WorkFromAnywhere
We hire talented, self-motivated people and get out of their way
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
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 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.
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.
Qualifications
Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Experience:
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.
Technical Skills:
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.
Soft Skills:
Strong problem-solving abilities and analytical thinking.
Excellent communication skills, both written and verbal.
Ability to work collaboratively in a team environment.
Self-motivated with a passion for continuous learning and improvement.
Preferred Qualifications
Machine Learning: Experience with machine learning algorithms and techniques. (python/notebooks/etc)
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.
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.
Compensation: Base pay range of $160,000 - $190,000 + Series B equity with tremendous upside potential + Attractive benefits
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.
ApplyJob Profile
Attractive benefits Continuous learning opportunities Equity Financial advisory Flexible paid time off Flexible schedule Fully remote Generous compensation Health insurance Learning stipend MacBook Pro Meal stipend Remote-first company Remote-first culture Remote work Social meet-up stipend Wellness stipend Work from Anywhere
Tasks- Analyze large datasets
- Develop backend services
- Document processes
- Ensure security compliance
- Implement device fingerprinting algorithms
- Integrate machine learning models
- Mentor junior team members
- Monitor browser technologies
- Optimize data collection
AI Algorithms AML AML Compliance Analytical APIs AWS Azure Backend Development Behavior biometrics CI/CD Collaboration Communication Compliance Data analysis Data processing Device intelligence DevOps Docker Fraud Prevention Go Golang Javascript Kubernetes Machine Learning Monitoring Non-relational databases Probabilistic Modeling Python Relational databases SQL Statistical analysis
Experience5 years
EducationBachelor's degree Computer Science Machine Learning Master's degree
TimezonesAmerica/Anchorage America/Chicago America/Denver America/Edmonton America/Los_Angeles America/Moncton America/New_York America/Regina America/St_Johns America/Toronto America/Vancouver Pacific/Honolulu UTC-10 UTC-3 UTC-4 UTC-5 UTC-6 UTC-7 UTC-8 UTC-9