Machine Learning Engineer
Advance Plaid’s foundation models by developing novel architectures, pretraining objectives, and fine-tuning strategies. Work across the full ML stack from data engineering to production serving and monitoring.
Responsibilities
- Building a foundation model on one of the world’s richest financial datasets
- Doing research that ships: moving from experimentation and prototypes to production systems serving real customers
- Working across the full ML stack, from pretraining objectives and architectures to serving infrastructure and monitoring
- Collaborating with a high-caliber team and seeing your work amplify the capabilities of multiple product teams
- Helping hundreds of millions of consumers achieve greater financial freedom through data-driven products
Requirements
- MS or PhD in ML/AI/CS/Stats/Applied Math (or closely related). PhD preferred but not required — candidates with equivalent industry research and production experience will be considered
- 1-3 years of industry experience building and deploying ML models, with evidence of both research depth and production delivery
- Strong applied ML research skills with production delivery experience
- Depth in Transformers/LLMs, representation learning, or large-scale model training
- Distributed training experience and strong Python + software engineering fundamentals
Nice-to-Haves
- Fintech / financial data domain experience
- Demonstrated ability to ship models to production (not just prototype)
- External publications or open-source contributions
Benefits
- Additional compensation in the form of equity and/or commission
- Comprehensive benefit plan, including medical, dental, vision, and 401(k)
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