Senior Software Engineer - ML Infrastructure in San Francisco

Energy Jobline is the largest and fastest growing global Energy Job Board and Energy Hub. We have an audience reach of over 7 million energy professionals, 400,000+ monthly advertised global energy and engineering jobs, and work with the leading energy companies worldwide.

We focus on the Oil & Gas, Renewables, Engineering, Power, and Nuclear markets as well as emerging technologies in EV, Battery, and Fusion. We are committed to ensuring that we offer the most exciting career opportunities from around the world for our jobseekers.

Job DescriptionJob DescriptionPlaid 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 of AI-powered financial experiences.

As a Senior Software Engineer on the Machine Learning Infrastructure team, you will design, build, and operate the systems that power machine learning across Plaid. You will apply your deep technical expertise to create scalable, reliable, and secure ML platforms, and collaborate closely with ML product teams to accelerate the delivery of ML & AI-powered products.

This is a highly technical, hands-on role where you’ll contribute to core infrastructure, influence architectural direction, and mentor peers while helping to define the “golden path” for ML development and deployment at Plaid.Responsibilities

• Design and implement large-scale ML infrastructure, including feature stores, pipelines, deployment tooling, and inference systems.
• Drive the rollout of Plaid’s next- 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.

Qualifications

The target base salary for this position ranges from $180,000 / year to $270,000 / year in Zone 1. The target base salary will vary based on the job's location.

Our geographic zones are as follows : Zone 1 - New York City and San Francisco Bay Area Zone 2 - Los Angeles, Seattle, Washington D.C.Zone 3 - Austin, Boston, Denver, Houston, Portland, Sacramento, San DiegoZone 4 - Raleigh-Durham and all other US cities

Additional compensation in the form(s) of equity and / or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.

If you are interested in applying for this job please press the Apply Button and follow the application process. Energy Jobline wishes you the very best of luck in your next career move.