onsite
Machine Learning Engineer Research Scientist - Plaid
ML Engineer
Research-focused Machine Learning Engineer responsible for designing, prototyping, and scaling advanced ML models and algorithms that power financial data services and developer tools.
About the role
Key Responsibilities
- Design, develop, and evaluate state‑of‑the‑art machine learning and deep learning models for financial data processing and risk analysis.
- Prototype novel research ideas, conduct experiments, and translate successful concepts into production‑ready services.
- Collaborate with data engineers and product teams to build scalable data pipelines and APIs on cloud infrastructure.
- Publish findings internally, contribute to open‑source projects, and stay current with emerging ML research.
- Monitor model performance in production, implement continuous improvement and bias mitigation strategies.
Requirements
- Strong proficiency in Python and experience with ML frameworks such as TensorFlow or PyTorch.
- Solid background in machine learning, deep learning, and statistical modeling, preferably applied to finance or large‑scale data.
- Hands‑on experience building data pipelines and deploying models on cloud platforms (e.g., AWS, GCP, Azure).
- Track record of research contributions—publications, patents, or open‑source work.
- Excellent problem‑solving skills and ability to work cross‑functionally in a fast‑moving environment.
Skills
pythontensorflowpytorchmachine learningdeep learningaws