Machine Learning Engineer

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.
  
  

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.

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.
• 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.
  
  

Required Qualifications

• 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.
• 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

• 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.