Senior Software Engineer - ML Infrastructure Jobs

Plaid

Location:
United States, San Francisco

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

180000.00 - 270000.00 USD / Year

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Job Description:

We build simple yet innovative consumer products and developer APIs that shape how everybody interacts with money and the financial system. Plaid is evolving into an AI-first company, where data and machine learning are the key enablers of smarter, more secure insight products built on top of Plaid’s vast financial data network. The Machine Learning Infrastructure team sits at the center of this transformation. We build the platforms that enable model developers to experiment, train, deploy, and monitor machine learning systems reliably and at scale — from feature stores and pipelines, to deployment frameworks and inference tooling. We are in the midst of a pivotal shift: replacing legacy systems with a modern feature store, and establishing a standardized ML Ops “golden path.” Our mission is to enable Plaid’s product teams to move faster with trustworthy insights, deploy models with confidence, and unlock the next generation of AI-powered financial experiences. As a Senior Software Engineer on the Machine Learning Infrastructure team, you will design, build, and operate the systems that power machine learning across Plaid. You will apply your deep technical expertise to create scalable, reliable, and secure ML platforms, and collaborate closely with ML product teams to accelerate the delivery of ML & AI-powered products. This is a highly technical, hands-on role where you’ll contribute to core infrastructure, influence architectural direction, and mentor peers while helping to define the “golden path” for ML development and deployment at Plaid.

Job Responsibility:

Design and implement large-scale ML infrastructure, including feature stores, pipelines, deployment tooling, and inference systems
Drive the rollout of Plaid’s next-generation feature store to improve reliability and velocity of model development
Help define and evangelize an ML Ops “golden path” for secure, scalable model training, deployment, and monitoring
Ensure operational excellence of ML pipelines and services, including reliability, scalability, performance, and cost efficiency
Collaborate with ML product teams to understand requirements and deliver solutions that accelerate experimentation and iteration
Contribute to technical strategy and architecture discussions within the team
Mentor and support other engineers through code reviews, design discussions, and technical guidance

Requirements:

5+ years of industry experience as a software engineer, with strong focus on ML/AI infrastructure or large-scale distributed systems
Hands-on expertise in building and operating ML platforms (e.g., feature stores, data pipelines, training/inference frameworks)
Proven experience delivering reliable and scalable infrastructure in production
Solid understanding of ML Ops concepts and tooling, as well as best practices for observability, security, and reliability
Strong communication skills and ability to collaborate across teams

Nice to have:

Experience with ML Ops tools such as MLFlow, SageMaker, or model registries
Exposure to modern AI infrastructure environments (LLMs, real-time inference, agentic models)
Background in scaling ML infrastructure in fast-paced product environments

What we offer:

medical, dental, vision, and 401(k)

Additional Information:

Job Posted:
December 11, 2025

Employment Type:

Fulltime

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Senior Software Engineer - ML Infrastructure