The posting
Job Description:
At Remitly, we are on a mission to transform lives by providing trusted financial services that transcend borders. We serve millions of customers sending billions of dollars each year across 170+ countries, and our work impacts communities on a truly global scale.
About the Role:
As a Staff Machine Learning Engineer in Remitly's Core AI/ML team, you'll work at the heart of our AI strategy. The Core AI/ML team is responsible for building the foundational machine learning systems, frameworks, and services that power Remitly's next generation of products and operations. We work horizontally across domains at Remitly—Global Money Movement, Treasury, Identity & Trust, Promotions, Referrals, etc.
We are looking for an experienced Machine Learning Engineer to build large scale systems that propel our next phase of growth.
You Will:
- Lead the end-to-end ML lifecycle from raw data to EDA to model training to offline/online evaluation and model deployment.
- Design, build, and scale feature pipelines for batch and real-time ML applications.
- Partner with data scientists, product owners, and engineers across verticals to turn prototypes into reliable, customer-facing ML systems.
- Optimize models and pipelines using MLOps best practices: automated retraining, drift detection, CI/CD, monitoring, observability.
- Mentor and lead other engineers: champion design reviews, technical discussions, and maintain a high bar for code quality.
- Drive technical strategy and influence ML architecture decisions across the organization.
You Have:
- Degree in Computer Science, Data Science, Statistics, Mathematics or equivalent practical experience.
- 10+ years delivering Machine Learning systems in production.
- Strong programming skills in Python, Go, Scala or a similar language.
- Hands-on experience with ML frameworks (e.g., PyTorch, scikit-learn, numpy).
- Experience working with major cloud platforms (AWS, GCP, or Azure).
- Experience with one or more of Deep Learning algorithms, Large Language Models, Causal Inference, Personalization, Knowledge Graphs, Natural Language Processing would be desirable.
- Experience with transformer architectures, pretraining, post-training, and fine-tuning of LLMs would be strongly preferred.
- Demonstrated experience leading cross-functional ML initiatives and mentoring senior engineers.
Compensation Details. The starting base salary range for this position is typically $208,000-$260,000. 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
Our Connected Work Culture: Driving Innovation, Together
At Remitly, we believe that true innovation sparks when we come together. Our Connected Work Culture fosters dynamic in-person collaboration, where ideas ignite and challenging problems find solutions faster. For corporate team members, we have an in-office expectation of at least 50% of the time monthly, typically achieved by coming in three days a week. This creates a consistent, meaningful overlap that supports team norms and business needs. Managers also have the flexibility to set higher expectations based on their team's specific needs. These intentional in-office moments are vital for deepening relationships, fueling creativity, and ensuring your impact is felt where it matters most.
Remitly is an E-Verify Employer
At Remitly, we are dedicated to ensuring that our workplace offers equal employment opportunities to all employees and candidates, in full compliance with applicable laws and regulations.
Remitly is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
