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 β 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