Lead the ML Infrastructure team to deliver and manage scalable machine learning systems, while fostering a culture of excellence and collaboration among engineers.
We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam.
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 the Engineering Manager for Machine Learning Infrastructure, you will be responsible for guiding a senior engineering team through the design, delivery, and operation of Plaid’s ML infrastructure. We are looking for a leader who combines deep technical expertise in ML infrastructure with proven experience scaling and managing senior engineering teams. You’ll ensure clarity of execution, help your team deliver high-quality systems, and partner closely with ML product teams to meet their needs. This role is execution-driven: you will translate strategy into action, remove blockers, and build a culture of ownership and technical excellence.
Responsibilities
- Lead and support the ML Infra team, driving project execution and ensuring delivery on key commitments.
- Build and launch Plaid’s next-generation feature store to improve reliability and velocity of model development.
- Define and drive adoption of an ML Ops “golden path” for secure, scalable model training, deployment, and monitoring.
- Ensure operational excellence of ML pipelines, deployment tooling, and inference systems.
- Partner with ML product teams to understand requirements and deliver solutions that accelerate model development and iteration.
- Recruit, mentor, and develop engineers, fostering a collaborative and high-performing team culture.
Qualifications
- 8–10 years of experience in ML infrastructure, including direct hands-on expertise as an engineer, IC/TL.
- 2+ years of experience managing infrastructure or ML platform engineers.
- Proven experience delivering and operating ML or AI infrastructure at scale.
- Solid technical depth across ML/AI infrastructure domains (e.g., feature stores, pipelines, deployment, inference, observability).
- Demonstrated ability to drive execution on complex technical projects with cross-team stakeholders.
- Strong communication and stakeholder management skills.
Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!
Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at [email protected].
Please review our Candidate Privacy Notice here.
Top Skills
AI
Feature Store
Infrastructure
Machine Learning
Ml Ops
Plaid San Francisco, California, USA Office
San Francisco, CA, United States, 94105
Similar Jobs
Automotive
Lead an ML Platform engineering team building large-scale GPU cluster architecture, training and inference orchestration, and performance optimization. Own design, scaling, scheduling, networking, and resource management while partnering with research and stack teams to accelerate production deployment and drive hiring and mentorship.
Top Skills:
Pytorch Distributed,Megatron-Lm,Deepspeed,Fsdp,Slurm,Kubernetes,Infiniband,Rdma,Gpu Clusters,Gpus,Mixed-Precision Training,Pipeline Parallelism,Tensor Parallelism,Data Parallelism,Checkpointing,Batching,Model Serving,Quantization,Compiler Optimizations
Aerospace • Information Technology • Software • Cybersecurity • Design • Defense • Manufacturing
The Associate Electrical Design Engineer will assist in designing ground support equipment, resolving manufacturing issues, and documenting electrical system requirements.
Top Skills:
CatiaComputer Aided Design (Cad)
Aerospace • Information Technology • Software • Cybersecurity • Design • Defense • Manufacturing
The role involves designing mechanical flight control systems, ensuring compliance with safety regulations, collaborating across teams, and managing airworthiness certifications.
Top Skills:
Catia V5Easy5EnoviaSimulink
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine


