Job Description:

Remitly’s vision is to transform lives with trusted financial services that transcend borders. Since 2011, we have been tirelessly delivering on our promises to people who send money around the world. Today, we are reimagining global financial services and building products that extend beyond traditional barriers to give customers access to more of the services they need, no matter where they call home. Join over 2,700 employees worldwide who are growing their careers with purpose and connection with our customers while having a positive impact on millions of people around the globe.

About the Role:

The Trust Machine Learning team protects Remitly's customers by developing intelligent systems that prevent fraud. These systems assess the risk of every transaction and customer interaction, while minimizing the impact on user experience and customer trust.

As a Senior Machine Learning Engineer, you will build feature engineering pipelines by integrating with rich data sources, optimize model performance by exploring new techniques and algorithms, and ensure the quality of live production models.

You will report to the Manager of Trust Machine Learning. This is a role with hybrid work schedule (2-3 days in office) to support team collaboration and is based in Remitly's office in Seattle, Washington.

You Will:

• Build scalable, reliable feature engineering pipelines for batch, streaming, and real-time features consumed by a diversity of machine learning models
• Design, implement, and maintain machine learning models and systems to identify risky transactions and behavior, mitigating platform abuse
• Optimize model performance, ensuring system reliability and model monitoring by championing MLOps best practices
• Lead and mentor peers through regular design reviews, architectural discussions, code reviews, and other technical activities

You Have:

• (A degree in computer science, data science, statistics, or related field (or equivalent experience)
• 5+ years of experience building and deploying machine learning and data systems
• 5+ years of programming experience in Python, Go, Scala, or equivalent
• 2+ years of experience using machine learning tools and frameworks (e.g., PyTorch, TensorFlow, or equivalent)
• 2+ years of experience with distributed or stream processing frameworks (e.g., Apache Spark, Apache Flink, Ray)
• Experience working with cloud platforms (e.g., AWS, GCP, Azure) and infrastructure-as-code (e.g., Terraform)

Compensation Details. The starting base salary range for this position is typically $180,000-$225,000. In the U.S., Remitly employees are shareholders in our Company and equity is part of our total compensation plan. Your recruiter can share more information about medical benefits offered, as well as other financial benefits and total compensation components offered with this role.

Our Benefits:

• Flexible paid time off
• Health, dental, and vision + 401k plan with company matching
• Paid parental, medical, military and family care leave
• Mental Health & Family Forming Benefits
• Employee Stock Purchase Plan (ESPP)
• Continuing education and travel benefits

We are committed to nondiscrimination across our global organization and in all of our business operations. Employment is determined based upon personal capabilities and qualifications without discrimination on the basis of race, creed, color, religion, sex, gender identification and expression, marital status, military status or status as an honorably discharge/veteran, pregnancy (including a woman’s potential to get pregnant, pregnancy-related conditions, and childbearing), sexual orientation, age (40 and over), national origin, ancestry, citizenship or immigration status, physical, mental, or sensory disability (including the use of a trained dog guide or service animal), HIV/AIDS or hepatitis C status, genetic information, status as an actual or perceived victim of domestic violence, sexual assault, or stalking, or any other protected class as established by law.

Remitly is an E-Verify Employer

Remitly is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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