Senior Machine Learning Engineer

Summary

The job description is for a Machine Learning Engineer role at a financial crime prevention company offering remote work and flexible hours. The position involves designing, developing, and implementing machine learning solutions to mitigate fraud and risk.

Requirements

• 5+ years of hands-on experience in Machine Learning or related roles within Fraud, Risk, Compliance, Payments, or FinTech domains
• Extensive knowledge and educational background in computer science, machine learning, and statistics
• Strong programming proficiency in Python and SQL, coupled with hands-on experience in backend development
• Proficiency in data warehousing, data pipelines, and ETL tools, with a proven track record of managing the machine learning lifecycle
• Experience with cloud computing platforms such as GCP, AWS, or Azure
• Familiarity with Kubernetes or Docker for efficient containerization
• Proven track record of collaboration with data scientists to build, deploy, and refine machine learning models
• Prior experience in building ML observability to uphold the performance and reliability of machine learning models in production

Responsibilities

• Design, develop, and implement machine learning models and algorithms utilizing Python and SQL
• Enhance backend systems for feature processing and model serving, optimizing efficiency and reliability
• Engage with large-scale data sets, data pipelines, and data warehousing tools to extract meaningful insights
• Collaborate with cross-functional teams to identify business challenges, devise solutions, and iteratively enhance machine learning models
• Establish and fortify ML observability to ensure machine learning models' steadfast performance and reliability in production
• Build scalable and efficient machine learning infrastructure utilizing advanced tools such as Vertex AI, Apache Beam, and Kubeflow
• Develop software systems and libraries to bolster machine learning applications and streamline integration
• Conduct experiments, execute statistical analyses, and assess model performance to optimize accuracy, reliability, and speed

Benefits

• Generous compensation in cash and equity
• 7-years for post-termination option exercise (vs. standard 90 days)
• Early exercise for all options, including pre-vested
• Work from anywhere: Remote-first Culture
• Flexible paid time 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