Senior Software Development Engineer

Sorry, this job was removed at 06:12 p.m. (CST) on Friday, Mar 21, 2025
Seattle, WA
In-Office
180K-225K Annually
eCommerce • Fintech • Payments • Software • Financial Services
We provide trusted digital financial services to our customers and recipients in over 170 countries across the globe.
The Role

Job Description:

About the Role:

We're looking for a Senior Engineer to help design, develop, and maintain the tooling and infrastructure platform that powers the next generation of scalable data science products. You will address a diverse range of data science and machine learning challenges, including those involving large language models (LLMs).

You'll collaborate with teams in the Machine Learning domain and partner with infrastructure teams to enhance existing systems, develop new features, and build entirely new platforms. These systems will support critical workflows such as model experimentation, training, deployment, serving, and evaluation, ensuring seamless integration and scaling of data science solutions. We support hybrid work, and you will work 50% of your time each month in our Seattle office. You will be reporting to the ML platform engineering Manager.

You Will:

  • Build backend services in Go on AWS
  • Be the backbone of critical systems such as Model Development, Feature Store, Experimentation and Model Deployment, ensuring seamless functionality and performance.
  • Collaborate with data scientists, ML engineers, and software engineers to support multiple domains and products across the company
  • Inspire creativity by optimizing infrastructure, improving reliability, and delivering tools that empower teams to solve complex challenges
  • Partner with product managers and engineers across teams to help achieve product and team goals

You Have:

  • 5 or more years of experience developing applications - preferably using Go or Java.
  • Experience working with machine learning platforms.
  • Experience with several of the following frameworks: SKLearn, XGBoost, PyTorch, and Tensorflow.
  • Experience with building batch model inference and online model serving systems.
  • Experience building and supporting Feature Store systems.
  • Experience designing and implementing orchestration systems for training and automating training workflows.
  • Have worked well with data scientists, business analysts and machine learning infrastructure to connect the dots between business and technology partners
  • Experience with CI/CD tools such as Jenkins, Maven, GitLa

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. #LI-Hybrid

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

What the Team is Saying

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The Company
HQ: Seattle, WA
2,800 Employees
Year Founded: 2011

What We Do

Since 2011, Remitly has been tirelessly delivering on our promises to our customers sending their hard earned money home. Today, we are incredibly proud to have served millions of customers globally. We strive daily to meet our promise to our customers by building peace of mind into everything we do. Join over 2,700 employees across 10 offices who are growing their careers while having a positive impact on people globally.

Why Work With Us

We are united through our vision to transform lives with trusted financial services that transcend borders. We accomplish our vision by relentlessly focusing on culture via our cultural values. That starts with putting customers at the center of everything we do, and includes investing in the growth & development of our team.

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Remitly Teams

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About our Teams

Remitly Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Our best work begins in moments when ideas spark, when we are deeply connected, and when we’re moving fast to solve challenging customer problems. These moments shape our culture. Our guidance is to committing to 3 days a week in the office.

Typical time on-site: 3 days a week
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