Senior Software Engineer - Network Enablement (Applied ML)

Plaid2 weeks ago

Location

San Francisco

Type

Full Time

Salary

USD 200,000 – 300,000

Level

Senior

Role

Senior Software Engineer

Posted

Feb 28, 2026

Full TimeSenior

The role

Summary

A Senior Software Engineering role at Plaid focusing on Network Enablement and Applied Machine Learning, responsible for building and operating ML infrastructure that powers trust and intelligence across Plaid's financial network. The role involves developing sophisticated ML pipelines, real-time scoring systems, and collaborative cross-functional ML product development.

What you'll do

ML Infrastructure Development: Design and implement robust ML infrastructure for real-time scoring, feature engineering, and model deployment across Plaid's network

Model Inference Integration: Embed model inference into product flows, APIs, and decision logic with comprehensive metric tracking and validation

Experimental ML Rollouts: Design and execute experimental rollout plans including backtesting, shadow scoring, A/B tests, and feature-flagged releases

Model Monitoring and Maintenance: Implement comprehensive model monitoring, drift detection, quality dashboards, and maintain model CI/CD processes

Cross-Functional Collaboration: Partner with Product, ML Platform, Fraud, and Privacy teams to scale network intelligence and develop auditable ML solutions

What we look for

Technical

Programming LanguagesAdvanced proficiency in Go or Python for backend services and ML infrastructure

Data Pipeline ToolsExpertise in batch and streaming data pipeline orchestration using Airflow or Spark

ML InfrastructureExperience with real-time scoring systems, feature stores, and low-latency model inference endpoints

Education

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

Experience

ML Operations5+ years of software engineering experience with strong focus on machine learning infrastructure and production ML systems

Skills

Required skills

ML InfrastructureAdvanced knowledge of model lifecycle management, CI/CD for models, and production ML deployment

System DesignStrong systems design skills with emphasis on building reliable, scalable backend services

Nice to have

Domain ExpertiseExperience in fraud, risk, or marketing intelligence domains

Advanced ML TechniquesKnowledge of graph frameworks, feature engineering, and sequence embeddings

Compensation & benefits

Salary

USD 200,000 – 300,000 (annual)

Stock options

Available

Benefits

Health Insurance

Comprehensive medical, dental, and vision coverage

Equity Compensation

Stock options and potential equity grants

Professional Development

Continuous learning opportunities and conference sponsorships

Interview process

1
Initial Screening — Phone or video call with recruiting team to discuss background and role fit
2
Technical Interview — Deep-dive into technical skills, system design, and ML infrastructure expertise
3
ML Systems Design Challenge — Comprehensive assessment of ML infrastructure design and problem-solving capabilities
4
Cross-Functional Team Interview — Meetings with potential teammates from Engineering, Product, and ML teams
5
Final Leadership Interview — Discussion with senior leadership about team vision and candidate's potential contribution