Senior Machine Learning Engineer (Research Scientist) - Data Foundation & AI

About the Role

The Data Foundation and AI team plays a critical role in transforming Plaid's financial network data into general-purpose representations that can be used by teams across the company. As a Senior Research Scientist, you will have the opportunity to collaborate with a high-caliber team and see your work amplify the capabilities of multiple product teams.

Plaid's mission is to unlock financial freedom for everyone, and as a Senior Machine Learning Engineer, you will be contributing to this mission by developing innovative solutions that empower thousands of developers to create their own products.

What You Will Do

• Design and develop foundation models, pretraining objectives, and fine-tuning strategies for various product use cases
• Build and maintain end-to-end production machine learning systems, including training pipelines, model serving infrastructure, feature engineering, and monitoring
• Collaborate with cross-functional teams to develop robust evaluation frameworks for assessing model performance across diverse tasks
• Develop and maintain large-scale machine learning models, including distributed training and deployment
• Work with the Data Foundation and AI team to transform Plaid's financial network data into general-purpose representations
• Design and implement data curation and preprocessing pipelines for machine learning models
• Develop and maintain software applications and tools to support machine learning model development and deployment
• Collaborate with product teams to integrate machine learning models into their products and services
• Stay up-to-date with the latest advancements in machine learning and AI, applying this knowledge to improve Plaid's machine learning capabilities

What We Are Looking For

• Strong applied machine learning research skills with production delivery experience
• Depth in Transformers/LLMs, representation learning, or large-scale model training
• Demonstrated ability to ship models to production, with experience in distributed training and deployment
• Strong Python and software engineering fundamentals, with experience in Agile development methodologies
• Experience working with fintech or financial data, with a strong understanding of the industry and its challenges
• Excellent communication and collaboration skills, with experience working with cross-functional teams
• Strong problem-solving skills, with the ability to think critically and outside the box
• Experience with cloud-based machine learning platforms, such as AWS or GCP
• Familiarity with machine learning frameworks, such as TensorFlow or PyTorch

Nice to Have

• Experience with natural language processing or computer vision
• Knowledge of containerization using Docker
• Familiarity with Kubernetes or other container orchestration tools
• Experience with automated testing and continuous integration/continuous deployment (CI/CD) pipelines
• Certification in machine learning or a related field

Benefits and Perks

• Competitive salary and equity package
• Comprehensive health, dental, and vision insurance
• Flexible paid time off and vacation policy
• Remote work stipend and home office setup support
• Access to cutting-edge technology and tools
• Opportunities for professional growth and development
• Collaborative and dynamic work environment
• Flexible working hours and remote work options
• Annual bonus and stock option grants
• Access to employee resource groups and diversity initiatives
• Free meals and snacks in the office, as well as a fully stocked kitchen
• On-site fitness classes and wellness programs
• Access to mental health resources and support
• Paid parental leave and family care benefits
• Employee recognition and reward programs
• Professional development opportunities, including training and education support
• Social events and team-building activities
• Community involvement and volunteer opportunities
• Access to the latest technology and gadgets
• Flexible and accommodating work environment
• Open communication and transparent company culture
• Recognition and rewards for outstanding performance
• Opportunities for career advancement and growth
• Collaborative and supportive team environment
• Access to a wide range of company resources and tools
• Professional certification and training programs
• Employee discounts and perks
• Access to exclusive events and networking opportunities
• A dynamic and innovative work environment
• A culture of innovation and experimentation
• A team that is passionate about making a difference
• The opportunity to work on challenging and complex problems
• The chance to collaborate with a talented and experienced team
• A company that values diversity, equity, and inclusion
• A culture that prioritizes teamwork, collaboration, and open communication
• The opportunity to make a real impact and drive meaningful change
• A company that is committed to making a positive difference in the world
• A team that is driven by a shared sense of purpose and mission
• The chance to work with cutting-edge technology and tools
• A culture that values innovation, creativity, and experimentation
• The opportunity to learn and grow with a talented and experienced team
• A company that offers a wide range of benefits and perks
• A culture that prioritizes employee well-being and satisfaction
• The chance to make a real difference and drive meaningful change
• A team that is passionate about making a positive impact
• A company that values diversity, equity, and inclusion
• A culture that values teamwork, collaboration, and open communication
• The opportunity to work on challenging and complex problems
• The chance to collaborate with a talented and experienced team
• A company that is committed to making a positive difference in the world

• Develop a strong portfolio that showcases your machine learning skills and experience, with a focus on applied research and production delivery.
• Make sure to highlight your ability to collaborate with cross-functional teams and drive innovation in your work.
• Be prepared to discuss your experience with machine learning frameworks, such as TensorFlow or PyTorch, and your ability to apply these skills to real-world problems.
• Emphasize your understanding of the fintech industry and its challenges, as well as your ability to think critically and outside the box.
• Practice your coding skills and be prepared to complete coding challenges or whiteboarding exercises during the interview process.
• Show your passion for machine learning and AI, and be prepared to discuss the latest advancements in the field and their potential applications.
• Highlight your experience working with large-scale datasets and your ability to develop and maintain distributed training and deployment pipelines.
• Be prepared to discuss your experience with cloud-based machine learning platforms, such as AWS or GCP, and your ability to apply these skills to real-world problems.
• Develop a strong understanding of the company culture and values, and be prepared to discuss how your skills and experience align with these.
• Prepare to talk about your experience with automated testing and continuous integration/continuous deployment (CI/CD) pipelines, and how you have applied these skills in previous roles.