Machine Learning Engineer

About the Role:
- Design and build machine learning systems for real-time fraud detection.
- Work across machine learning, backend engineering, and data infrastructure.
- Own end-to-end ML solutions from data processing to production deployment.
- Build scalable, reliable, and efficient systems for high-stakes fraud prevention.

Responsibilities:
- Build and optimize real-time data pipelines for device and behavioral data.
- Develop, deploy, and maintain production ML models for fraud detection.
- Engineer production-ready features from raw data.
- Collaborate with backend and platform engineers to integrate ML systems.
- Monitor model performance and iterate based on production feedback.
- Maintain security, privacy, and compliance standards.
- Follow best practices for testing, documentation, and observability.

Required Qualifications:
- Experience: 5–8 years of software engineering experience.
- Strong backend engineering experience with Go or Python.
- Hands-on experience building applied machine learning solutions using large datasets.
- Experience owning end-to-end ML systems, including feature engineering and pipelines, model deployment, production monitoring, and continuous model improvement.
- Experience building latency-sensitive ML systems serving real-time predictions at scale.
- Strong backend engineering mindset with production system experience.
- Experience in fraud detection, including areas such as bot detection, device fingerprinting, and VPN and proxy detection.

Technical Skills:
- Go or Python.
- PyTorch or Scikit-learn.
- SQL.
- Relational and NoSQL databases.
- Feature pipelines.
- Model monitoring and drift detection.
- Docker.
- Kubernetes.

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

Soft Skills:
- Strong written and verbal English communication.
- Self-directed and comfortable working with minimal supervision.
- Able to navigate ambiguity and deliver independently.

Preferred Qualifications:
- Stronger backend engineering background than data science.
- Experience with CI/CD pipelines.
- Knowledge of browser APIs and high-entropy data collection techniques.
- Experience using frontier LLMs for automation.
- Ability to quickly learn new programming languages.

Compensation:
- Salary: $175K–$220K.
- Competitive equity.

Employment Details:
- Full-time.
- Remote-first within the United States or Canada.
- Hiring 3 candidates.

Locations:
- New York.
- San Francisco.
- South Bay Area.
- Los Angeles.

Visa Eligibility:
- No H-1B sponsorship.
- TN visa supported.
- L-1 and O-1 considered on a case-by-case basis.

Tech Stack:
- Go.
- Python.
- SQL.
- Docker.
- Kubernetes.

Location: Remote - USA, Canadá

Skills required for this job:

• Backend engineering
• Computer science
• Data pipelines
• Data processing
• Fraud detection
• Go
• MLOps
• Machine learning
• Python
• SQL
• Software engineering