Machine Learning Engineer

Selby Jennings is working with a Series D FinTech startup with over $1 billion in valuation. The firm propelled to unicorn status in just five years going from seed stage to series D. Their mission is to make capital more affordable for everyone by leveraging technology to minimize transaction costs. They have designed the most convenient, transparent, and cost-effective credit card specifically for homeowners.

The Team

The team is composed of experienced professionals from both finance and technology industries. The company was established by former engineering executives at Facebook and Square with engineering degrees from MIT and University of Waterloo. Key players have backgrounds with renowned companies such as Goldman Sachs, SoFi, Square, Microsoft, and Facebook, while investors include top-tier firms like Founders Fund, Sequoia, and Khosla Ventures. The company is actively searching for exceptional talent to help build and refine its vision. Their collective experience includes:

• Financial products (e.g., Square/Cash App, early CapitalOne credit cards)
• Consumer products (e.g., Facebook, Xbox)
• Technology infrastructure (e.g., C++/C#, Visual Studio, Windows, Azure

Who They're Looking For

The company is seeking an experienced Machine Learning Engineer who thrives on solving complex, multifaceted problems and has a deep understanding of all parts of a system. The ideal candidate will take ownership of performance issues, debug race conditions across client-server interactions, and lead efforts in system architecture, design, and code reviews. Over time, this role will evolve to include significant technical leadership responsibilities.

• Working as part of our team researching and engineering ML systems.
• Training large neural networks and machine learning systems at scale in HPC clusters
• Architecting and implementing ML training, validation, and inference pipelines from idea to product
• Researching and implementing state of the art algorithms from literature
• Using good software engineering practices to write production-grade software
• Innovating and defining novel creative solutions to deep problems using first-principles thinking, and communicating your ideas to the team

Requirements

• Strong ML background with exposure to transformers based architectures. RL, graphs/GNNs and MuZero style patterns are a plus.
• Proven track record in writing scalable, performant and clean python code for production and developing effective ML pipelines from initial idea to deployable product

Employment

• Office based in San Francisco
• Competitive salary and stock
• Excellent health benefits and a matched 401(k) plan
• Opportunity to publish research and co-author patents

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