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STOITECH

Staff Machine Learning Engineer

STOITECH, Seattle, Washington, us, 98127


Are you passionate about using

machine learning

to improve people's lives?

Our client is a growing

FinTech

startup (Series A funded, ~50 employees) building innovative products that empower everyday consumers to manage their finances. Join their mission-driven

Data Science

team and make a tangible impact!

What You'll Do:

Design and develop cutting-edge AI models to power the company's FinTech solutions (think fraud detection, financial growth tools, etc.).

Collaborate closely with the data science team (including Staff Data Scientists), product managers, and engineers to bring their models to life.

Stay on top of the latest AI research and integrate those advancements into their work.

Manage projects independently, ensuring timely and successful completion of deliverables.

Communicate complex technical concepts to a diverse team with varying levels of machine learning expertise.

Contribute to the development and growth of the data science function within the company.

Why You'll Love It Here:

Fast-paced, high-growth environment:

Make a real impact on a growing

startup .

Exceptional learning & development:

Work alongside experienced data scientists and hone your skills.

Meaningful work:

Apply your expertise to

build models

that improve people's

financial

well-being.

State-of-the-art data infrastructure:

Leverage clean, well-organized

datasets

and advanced tooling.

Who You Are:

Master's

degree or

PhD

in

Computer Science ,

Physics ,

Mathematics ,

Engineering , or a related field.

5+ years of hands-on experience in

data science ,

deep learning , and

neural networks .

Experience in a deep learning framework (PyTorch/TensorFlow).

Extensive experience with at least 1 cloud computing provider (GCP preferred).

Strong analytical and problem-solving skills.

Excellent communication and teamwork skills.

Passion for AI, finance, and building something that makes a difference.

Ready to Make a Difference?

If you're a

machine-learning

rockstar who thrives in a collaborative environment and wants to use your skills for good, we want to hear from you!

Please note:

This is a full-time, in-office position in Seattle, WA, or San Francisco, CA.

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