Engineering Manager - Machine Learning Infrastructure

Plaid2 weeks ago

Location

San Francisco

Type

Full Time

Salary

USD 250,000 – 350,000

Level

Manager

Role

Engineering Manager

Posted

Feb 28, 2026

Full TimeManager

The role

Summary

Plaid seeks an Engineering Manager to lead its Machine Learning Infrastructure team, driving the development of cutting-edge ML platforms that enable rapid, reliable model development and deployment. The ideal candidate will combine deep technical expertise in ML infrastructure with strong leadership skills to transform Plaid's AI capabilities and support the company's mission of empowering financial innovation.

What you'll do

Team Leadership: Lead and support the Machine Learning Infrastructure team, driving project execution and ensuring delivery on critical commitments.

Feature Store Development: Build and launch Plaid's next-generation feature store to improve reliability and velocity of machine learning model development.

ML Ops Strategy: Define and drive adoption of a standardized ML Ops 'golden path' for secure, scalable model training, deployment, and monitoring.

Operational Excellence: Ensure high-performance and reliability of ML pipelines, deployment tooling, and inference systems.

Cross-Team Collaboration: Partner closely with ML product teams to understand requirements and deliver solutions that accelerate model development and iteration.

Talent Development: Recruit, mentor, and develop engineers, fostering a collaborative and high-performing team culture.

What we look for

Technical

ML Infrastructure ExpertiseDeep technical knowledge across ML/AI infrastructure domains including feature stores, pipelines, deployment, inference, and observability systems.

System ArchitectureProven experience in designing and operating large-scale ML and AI infrastructure platforms.

Education

Advanced DegreeBachelor's or Master's degree in Computer Science, Machine Learning, Software Engineering, or related technical field preferred.

Experience

Management ExperienceMinimum 2+ years of experience managing infrastructure or ML platform engineering teams.

Technical Leadership8-10 years of experience in ML infrastructure, including direct hands-on engineering and technical leadership roles.

Skills

Required skills

Machine Learning InfrastructureExpert-level understanding of ML platform architecture, feature engineering, and model deployment strategies.

Technical LeadershipAbility to drive complex technical projects and manage cross-functional stakeholder relationships.

Team ManagementStrong skills in recruiting, mentoring, and developing high-performance engineering teams.

Nice to have

Cloud PlatformsExperience with AWS, GCP, or Azure ML infrastructure and services.

MLOps ToolsFamiliarity with advanced MLOps tools like Kubeflow, MLflow, or similar platforms.

Compensation & benefits

Salary

USD 250,000 – 350,000 (annual)

Stock options

Available

Benefits

Health Insurance

Comprehensive medical, dental, and vision coverage

Equity Package

Competitive stock options and RSU grants

Flexible Work

Hybrid work environment with potential remote options

Professional Development

Ongoing learning and career growth opportunities

Wellness Program

Mental health resources and wellness benefits

Interview process

1
Initial Screening — Phone or video call with recruiting team to assess background and experience
2
Technical Interview — In-depth discussion of ML infrastructure expertise and technical leadership experience
3
Leadership Assessment — Behavioral interview focusing on team management and cross-functional collaboration
4
Final Executive Interview — Meeting with senior engineering leadership to evaluate strategic alignment