Who we are:

Sardine has built a behavior-based platform for fraud prevention, regulatory compliance, and instant payments. Led by a team of industry veterans, and fraud experts from PayPal, Zelle, Revolut, Chase, and Coinbase, the company has quickly grown to over 200 global customers. Sardine has raised $75M, led by Andreessen Horowitz Growth, XYZ Capital, Google Ventures, Visa, Activant Capital, Experian, and ING Ventures.

Our culture:

• We have hubs in the Bay Area, NYC, and Toronto. However, we have a remote-first work culture. #WorkFromAnywhere

• We hire talented, self-motivated people and get out of their way

• We value performance and not hours worked. We believe you shouldn't have to miss your family dinner, your kid's school play, or doctor's appointment for the sake of adhering to an arbitrary work schedule

Location:

• United States or Canada (From Home / Beach / Mountain / Cafe / Anywhere!)

• We are a remote-first company with a globally distributed team. So you can find your productive zone and work from there.

About the role:

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. You will work closely with cross-functional teams, including data scientists, software engineers, data analysts, account managers, and product managers, to deliver high-quality solutions.

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 and create solutions that leverage machine learning

• Help ship and refine machine learning models, working closely with data scientists

• 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 Apache Beam

• 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

• Stay up-to-date with the latest advancements in machine learning and related technologies

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

• Experience in Java, Go, and TypeScript is a plus

• Experience with infrastructure as code tools like Terraform is a plus

• Familiarity with Kubernetes or Docker for containerization

• Excellent problem-solving, analytical, and communication skills

• Passion for machine learning and its applications in real-world scenarios

• 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

Compensation: Base pay range of $120,000 - $170,000 + Series B equity with tremendous upside potential + Attractive benefits

Benefits we offer:

• 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

• Unlimited paid time off and minimum two weeks/year of mandatory vacation

• 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

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.

Compensation Range: $120K - $170K