Senior Machine Learning Engineer

Remitly; Burnaby; On-site; CAD 120,000 - 180,000; Full time

Benefits offered by this job

Education stipend

Office spaces for collaboration

Generous paid time off

DEI learning resources

Volunteer opportunities

Job summary

Remitly is seeking a Senior Machine Learning Engineer to join its Core AI/ML team in Burnaby. You will lead end-to-end ML lifecycle, build scalable feature pipelines, and collaborate with data scientists, product owners, and engineers to turn prototypes into reliable, customer-facing ML systems.

You will optimize models using MLOps practices, mentor engineers, and contribute to design reviews. The role requires hands-on experience with DL algorithms, LLMs, cloud platforms, and Python/Go/Scala.

Qualifications

• Experience delivering ML systems in production.
• Experience with one or more of Deep Learning algorithms, Large Language Models, Casual Inference, Personalization, Knowledge Graphs, Natural Language Processing would be desirable
• Experience working with major cloud platforms (AWS, GCP, or Azure).

Responsibilities

• 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.
• Mentor and lead other engineers: champion design reviews, technical discussions, and maintain a high bar code quality.

Skills

Python

Go

Scala

PyTorch

Scikit-learn

Numpy

Education

Bachelor's degree in Computer Science/Data Science/Statistics/Mathematics or equivalent

Tools

AWS

GCP

Azure

Job description

• As a Senior 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
• 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 code quality

Benefits

• Spend up to $1,000 per year on costs related to continuing education or on travel to countries Remitly serves, allowing you to gain insights to our customer’s journeys
• All of our office spaces offer our employees a place to collaborate and celebrate. With locally sourced artwork and vibrant designs, they create an environment that all can enjoy
• Fill your cup up outside of work and take advantage of our generous paid time off policies, leave policies, and flex working hours to ensure you are able to meet the demands of life outside of work
• Tap into the learning routines, resources and affinity groups Remitly provides to help you further your own DEI journey
• Contribute to the communities we serve through volunteering, employee giving, or civic advocacy
• Remitly provides rich benefit plans intended to cover the needs of our diverse teammates

We are looking for an experienced Machine Learning Engineer to build large scale systems that propel our next phase of growthExperience with one or more of Deep Learning algorithms, Large Language Models, Casual Inference, Personalization, Knowledge Graphs, Natural Language Processing would be desirableExperience working with major cloud platforms (AWS, GCP, or Azure)8+ years delivering Machine Learning systems in productionDegree in Computer Science, Data Science, Statistics, Mathematics or equivalent practical experienceStrong programming skills in Python, Go, Scala or a similar languageHands-on experience with ML frameworks (e.g., PyTorch, scikit-learn, numpy)