Machine Learning Engineer

December 23, 2023

Sardine

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Combine risk, compliance, and payment protection to increase customer trust and loyalty - all from one powerful API.

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Description

As a Machine Learning Engineer, you will be responsible for designing, developing, and implementing machine learning and feature engineering infrastructure that allows our company and clients to minimize losses associated with fraud and risk. To deliver high-quality solutions, you will work closely with cross-functional teams, including data scientists, software engineers, data analysts, account managers, and product managers. You will: • Design, develop, and implement machine learning models and algorithms using Python and SQL • Help improve our backend systems for feature processing and model serving • Work with large-scale data sets, data pipelines, and data warehousing tools • Collaborate with data scientists and other stakeholders to identify business problems, create solutions, and ship and refine machine learning models. • Build out our ML observability to ensure the performance and reliability of machine learning models in production. • Build scalable and efficient machine learning infrastructure using tools like Vertex AI, Apache Beam, and kubeflow. • Develop software systems and libraries to support machine learning applications. • Conduct experiments, perform statistical analysis, and evaluate model performance to improve accuracy, reliability, and speed.

Requirements

An ideal candidate has: • 5+ years of experience working in Machine Learning or similar roles • Extensive knowledge and educational background in computer science, machine learning, and statistics • Strong programming skills in Python and SQL • Hands-on experience in backend development • Experience in Industry: Fraud / Risk / Compliance / Payments / Crypto / FinTech • Proficiency in data warehousing, data pipelines, and ETL tools • Experience managing the machine learning lifecycle • Experience with cloud computing platforms like GCP, AWS, or Azure • Familiarity with Kubernetes or Docker for containerization • Experience working with data scientists to build and refine machine learning models • Experience building ML observability to ensure the performance and reliability of machine learning models in production

Benefits

• Generous compensation in cash and equity • 7-year 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 • 100% of health insurance, dental, and vision coverage for employees and 60% for dependents - US specific • 4% matching in 401k - US specific • Company-wide offsites, the last one was at Miami • MacBook Pro delivered to your door • One-time stipend to set up a home office — desk, monitors, etc. • Monthly meal stipend • Annual health and wellness stipend • Monthly meet-up stipend • Annual Learning stipend • Unlimited access to an expert financial advisory