Senior Software Engineer - ML Infrastructure

• 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

• 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

• 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

medical, dental, vision, and 401(k)