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SalaryJob Description:
About the Role
At Remitly, our Central Machine Learning Team plays a pivotal role in empowering various business verticals through cutting-edge Machine Learning solutions. As a Senior Machine Learning Engineer, you will be at the forefront of this endeavor, collaborating closely with diverse teams such as Customer Success and Treasury. Your expertise will drive the development and implementation of advanced ML models, addressing complex challenges and significantly contributing to our business goals.
You Will:
- Build models that make better customer experience and improve the self serve.
- Build Machine Learning models that detect malicious activity and actors in our system
- Work with the ML infrastructure team to ensure models can meet latency and uptime requirements
- Build end to end ML pipeline to train and deploy the models from development to production
- Mentor other MLEs and Data Scientists to elevate the overall expertise of the team
- Collaborate with leadership to set our ML Program and strategy vision
You Have:
- Bachelor’s degree in a quantitative field or equivalent experience
- 5+ years experience building production Machine Learning systems (experience with classification problems, time Series)
- At least 1+ of experience in LLM
- Candidates should have hands-on experience with Python and ML libraries (e.g., scikit-learn, scipy, numpy, matplotlib, pandas etc), SQL, and Spark.
- Work in tandem with teams like Customer Success and Treasury to deeply understand their unique challenges and objectives. Forge strong partnerships with Product Managers and Analysts to identify critical trends and patterns that can be leveraged for Machine Learning solutions
- Experience making tough technical tradeoffs. You sweat the details to understand the impacts of these tradeoffs and find a careful balance between short-term outcomes and long-term effects.
Remitly is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
