Engineering

Experienced Software Engineer - ML Infra Platform

United States | Full-time

We build simple yet innovative consumer products and developer APIs that shape how everybody interacts with money and the financial system.

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. #LI-Remote

The Machine Learning Platform team at Plaid is at the forefront of transforming the financial technology landscape. Specializing in developing cutting-edge machine learning products, this team plays a crucial role in advancing transaction enrichment, credit, and risk management solutions. By leveraging consumer-permissioned financial data, the team enables Plaid and its partners to craft innovative financial services that cater to the evolving needs of consumers and businesses alike.

As an Experienced Software Engineer on the Machine Learning (ML) Platforms team at Plaid, you will play a pivotal role in architecting and developing the core infrastructure that powers Plaid's machine learning initiatives. Your work will directly contribute to the innovation and effectiveness of ML products in areas such as transaction enrichment, credit evaluation, and risk assessment. If you're interested in helping build the state of art AI/ML solutions to unblock financial freedom for everyone, let's chat!

Responsibilities

  • Architecting Scalable ML Infrastructure: You will design and develop scalable, efficient, and robust machine learning infrastructure that supports the lifecycle of ML models—from data ingestion and processing to training, evaluation, and deployment. This infrastructure must be capable of handling large-scale data and complex computations with high reliability and performance
  • Improving ML Operations (MLOps): You will innovate and implement best practices in MLOps to streamline the development, deployment, and monitoring of ML models. This includes automating pipelines, ensuring model reproducibility, and facilitating seamless model versioning and rollout
  • Cross-Functional Collaboration: You will collaborate with product managers, data scientists, and other engineering teams to understand their needs and translate them into ML platform capabilities. This collaborative approach ensures that the ML infrastructure effectively supports product features and business objectives
  • Mentorship and Leadership: You will mentor junior engineers and peers, sharing your knowledge and expertise to promote a culture of technical excellence. Your leadership will help develop the team's skills and foster innovation
  • Staying Ahead of the Curve: You will keep abreast of the latest developments in machine learning, data engineering, and cloud technologies. By staying informed about industry trends and challenges, you will ensure that Plaid's ML platform remains cutting-edge and competitive

Qualifications

  • 8+ years of Software Engineering Experience
  • 3+ years with machine learning or developing machine learning platforms
  • Strong communication and architecture skills
  • Python experience and k8s experience
  • Have been in the ML space as a DS / MLE or as a SWE heavily supporting them
  • Have previous experience developing machine learning platforms / frameworks / infrastructure
  • Strong communication and architecture skills
  • Python experience and k8s experience

Target base salary for this role is between $182,520 and $297,000 per year. 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.
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 accommodations@plaid.com.

Please review our Candidate Privacy Notice here.

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Our headquarters is in sunny SOMA and includes a beautiful sun-filled atrium, a private outdoor deck and even a (semi-hidden) climbing wall.

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