Senior Machine Learning Engineer - Payments

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1 month ago
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Senior Machine Learning Engineer

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Overview

Senior Machine Learning Engineer - Payments — Plaid, Remote

We are seeking a Senior Machine Learning Engineer to join Plaid’s payments-focused ML team. Plaid builds tools and experiences used by thousands of developers to create financial products, enabling millions of users to connect their financial accounts to apps and services. Plaid powers connections with thousands of financial institutions across the US, Canada, the UK and Europe. Plaid was founded in 2013 and is headquartered in San Francisco with offices in New York, Washington, D.C., London and Amsterdam.

Salary range and location:

Full-time position with a base salary ranging from $225,600/year to $337,200/year (zone-based). Pay and benefits are subject to change and location considerations apply.

Responsibilities
  • Build with impact. Your work will empower millions of users through well-known and emerging Fintech applications with access to financial services.
  • Experiment with cutting-edge ML modeling techniques.
  • Work on both 0-1 stage problems as well as 1-10.
  • Develop AI/ML models in a full lifecycle, from offline training to online serving and monitoring.
  • Collaborate with teams across Plaid to define the ML roadmap.
  • Dive deep into data and apply data-driven decisions in day-to-day work.
  • Demonstrate high ownership in a bottom-up driven team.
Qualifications
  • 5+ years in training and serving AI/ML models in a production environment.
  • Experience building/working with data-intensive backend applications in large distributed systems.
  • Ability to code and iterate independently on data infrastructure tools like Python, Spark, Jupyter notebooks, standard ML libraries, etc.
  • Take pride in ownership and driving projects to business impact.
  • Data analytics and data engineering experience is a plus.
  • Experience with NLP applications is a plus.
  • Experience in the FinTech industry is a plus.
  • Ability to work with technical and non-technical teams.
  • Master\'s degree or equivalent work experience in Computer Science, Mathematics, Engineering, or a closely related field.
Compensation and Geography

The target base salary for this position ranges from $225,600/year to $337,200/year in Zone 1. The target base salary will vary based on the job\'s location. Our geographic zones are:

  • 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 Diego
  • Zone 4 - Raleigh-Durham and all other US cities
Additional compensation and benefits

Additional compensation in the form 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 scope and responsibilities, candidate experience and skillset, and location. Pay and benefits are subject to change at any time, in accordance with applicable plans.

About Plaid and Equal Opportunity

Our mission is to unlock financial freedom for everyone. Plaid seeks a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We encourage you to apply even if your experience doesn’t fully match the job description. Plaid is an equal opportunity employer and values diversity. We do not discriminate based on race, color, national origin, ethnicity, religion or belief, sex (including pregnancy or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other legally protected characteristics. We also consider qualified applicants with criminal histories as required by applicable laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need assistance, please contact . Please review our Candidate Privacy Notice here.


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