Senior Software Engineer - ML Infrastructure
WFA Digital Insight
As the demand for AI-powered financial experiences grows, Plaid is at the forefront of this shift. With a 30% increase in machine learning investments in 2025, skilled engineers are in high demand. This senior software engineer role offers a unique chance to drive the development of Plaid's ML infrastructure, working with a team of innovators to unlock financial freedom for everyone. Before applying, candidates should be aware of the evolving AI landscape and the importance of scalable, reliable infrastructure in driving business success.
Job Description
About the Role
The Senior Software Engineer - ML Infrastructure role at Plaid is a highly technical, hands-on position that requires a deep understanding of machine learning infrastructure and a passion for driving innovation. As a senior engineer on the Machine Learning Infrastructure team, you will design, build, and operate the systems that power machine learning across Plaid, collaborating closely with ML product teams to accelerate the delivery of ML & AI-powered products.The Machine Learning Infrastructure team is central to Plaid's transformation 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. You will apply your expertise to create scalable, reliable, and secure ML platforms, influencing architectural direction and mentoring peers to define the 'golden path' for ML development and deployment at Plaid.
What You Will Do
- 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
- Develop and maintain technical documentation for ML infrastructure and tools
- Participate in on-call rotations to ensure the reliability and uptime of ML systems
What We Are Looking For
- 5+ years of industry experience as a software engineer, with a 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 cloud-based technologies such as AWS or GCP
- Familiarity with containerization using Docker and Kubernetes
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
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
- Experience with Agile development methodologies and version control systems like Git
Benefits and Perks
- Competitive salary and equity package
- Comprehensive health, dental, and vision insurance
- Flexible PTO and paid holidays
- Remote work stipend and home office setup support
- Access to professional development and training opportunities
- Collaborative and dynamic work environment with a team of innovators
- Opportunity to work on cutting-edge ML infrastructure and drive business success
- Recognition and rewards for outstanding performance and contributions
- Comprehensive retirement savings plan with company match
- Employee wellness programs and mental health support
- Regular team-building activities and social events
- Access to the latest technologies and tools
- Opportunity to work with a diverse and talented team
- Professional growth and career advancement opportunities
- Flexible working hours and remote work options
- Employee stock purchase plan
- Education assistance and tuition reimbursement
How to Stand Out
- Develop a strong portfolio showcasing your experience with ML infrastructure and large-scale distributed systems
- Familiarize yourself with Plaid's technology stack and be prepared to discuss how you can contribute to the company's mission
- Highlight your ability to collaborate with cross-functional teams and drive technical direction
- Be prepared to discuss your experience with ML Ops tools and best practices for reliability, security, and scalability
- Show enthusiasm for the company's mission to unlock financial freedom for everyone and highlight your passion for driving innovation in the field of ML infrastructure
- Research the company culture and be prepared to discuss how you can thrive in a remote work environment
- Review the job description carefully and be prepared to discuss your experience and skills in relation to the required qualifications
- Prepare to discuss your experience with cloud-based technologies, containerization, and Agile development methodologies
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