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Staff Machine Learning Engineer

3 months ago

Seattle, Washington, United States STOITECH Full time
Are you passionate about using machine learningto improve people's lives?Our client is a growingFinTechstartup(Series A funded, ~50 employees) building innovative products that empower everyday consumers to manage their finances. Join their mission-drivenData Scienceteam 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 growingstartup.
  • Exceptional learning & development:Work alongside experienced data scientists and hone your skills.
  • Meaningful work:Apply your expertise tobuild modelsthat improve people'sfinancialwell-being.
  • State-of-the-art data infrastructure:Leverage clean, well-organizeddatasetsand advanced tooling.

Who You Are:

  • Master'sdegree orPhDinComputer Science,Physics,Mathematics,Engineering, or a related field.
  • 5+ years of hands-on experience indata science,deep learning, andneural 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 amachine-learningrockstar 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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