Senior Machine Learning Engineer (Research Scientist) - DFAI

About the Role

The day-to-day responsibilities will include building and maintaining production-grade ML systems end-to-end, collaborating with high-caliber teams, and seeing the impact of the work amplify the capabilities of multiple product teams. This is a unique chance to work on one of the world's richest financial datasets, doing research that ships and moves from experimentation and prototypes to production systems serving real customers.

Given the company's mission to unlock financial freedom for everyone, the Senior Machine Learning Engineer will play a pivotal role in making the financial ecosystem more equitable. The role's impact will be felt across the organization, and the ideal candidate should be driven by a desire to make a significant difference in people's financial lives.

What You Will Do

• Design, develop, and deploy foundation models that generalize across a wide range of downstream product use cases
• Build and maintain production-grade ML systems, including training pipelines, model serving infrastructure, feature engineering workflows, and monitoring systems
• Develop robust evaluation frameworks to measure model quality across diverse tasks and real-world applications
• Collaborate with product and engineering teams to adapt foundation models to specific business needs and validate their impact through rigorous experimentation
• Communicate and publish research findings internally and externally to advance the state of machine learning and AI across the organization
• Lead applied research efforts, focusing on designing model architectures, pretraining objectives, and fine-tuning strategies
• Work across the full ML stack, from pretraining objectives and architectures to serving infrastructure and monitoring
• Ensure the reliability and impact of AI-driven experiences at scale
• Contribute to the development of Plaid's shared machine learning and AI infrastructure
• Participate in the full lifecycle of ML systems, from data curation and model development to production serving, evaluation, and monitoring
• Stay updated with the latest advancements in machine learning and AI, incorporating new techniques and technologies into the role as appropriate

What We Are Looking For

• MS or PhD in ML/AI/CS/Stats/Applied Math (or closely related), with a preference for a PhD
• 3-7 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
• Demonstrated ability to ship models to production, not just prototype
• Distributed training experience and strong Python + software engineering fundamentals
• Experience working with fintech or financial data domain
• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams
• Strong problem-solving skills, with the ability to approach complex problems from multiple angles
• Experience with cloud-based technologies and containerization (e.g., Docker)

Nice to Have

• External publications or open-source contributions in the field of machine learning or AI
• Experience with large-scale data processing and storage solutions (e.g., Hadoop, Spark)
• Knowledge of agile development methodologies and version control systems (e.g., Git)
• Participation in machine learning competitions or hackathons
• Experience with automated testing frameworks and continuous integration/continuous deployment (CI/CD) pipelines

Benefits and Perks

• Competitive salary and equity package
• Comprehensive health, dental, and vision insurance
• Flexible PTO policy and remote work options
• Access to cutting-edge technologies and tools
• Opportunities for professional growth and development
• Collaborative and dynamic work environment
• Access to mental health resources and employee assistance programs
• Discounts on products and services from partner companies
• Participation in company-wide hackathons and innovation challenges

• Ensure your portfolio showcases applied research skills and production delivery experience, highlighting specific examples of ML models you've developed and deployed.
• Familiarize yourself with Plaid's products and services, and be prepared to discuss how your skills and experience align with the company's mission and goals.
• Develop a strong understanding of the fintech industry and the role of machine learning in driving innovation and growth.
• Practice explaining complex technical concepts in simple terms, as effective communication is crucial for success in this role.
• Be prepared to discuss your experience working with large datasets and distributed training, and how you've handled challenges in these areas.
• Consider reaching out to current or former Plaid employees for insights into the company culture and what it's like to work there.