Plaid

Senior Machine Learning Engineer - Credit

Plaid$130K — $180K *
Finance & Insurance
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 6+ years of experience in production environments training and serving AI and machine learning models
  • Experience in fintech lending with knowledge of model construction in that domain
  • Familiarity with data-intensive backend applications in large distributed systems
  • Proficient in coding independently with Python, Spark, Jupyter notebooks, and standard machine learning libraries
  • Strong ownership mindset and proven ability to drive projects to deliver business outcomes
  • Effective communication with both technical and non-technical teams
  • Master's degree or related experience in Computer Science, Mathematics, Engineering, or similar field
  • Desirable: experience in data analytics and data engineering

Responsibilities

  • Build machine learning systems that provide access to financial services for millions of users
  • Experiment with advanced machine learning modeling techniques for critical credit applications
  • Tackle both nascent projects and the scaling of existing systems
  • Develop machine learning models throughout their lifecycle, from training to deployment
  • Design, create, and implement scalable machine learning solutions and systems
  • Work collaboratively with cross-functional teams to shape the ML roadmap
  • Utilize data-driven decision-making in everyday tasks
  • Exercise high ownership while working within a bottom-up team structure

Benefits

  • Comprehensive medical, dental, and vision coverage
  • 401(k) retirement plan
  • Equity and/or commission compensation based on the role
  • Support for diverse backgrounds and experiences in hiring
  • Emphasis on building an equitable financial ecosystem
Full Job Description
Plaid's Data team is building models that improve how millions of users understand and grow their financial lives. We're looking for machine learning engineers with experience applying state-of-the-art machine learning and modeling techniques, including natural language processing, anomaly detection, optimization, and time series forecasting, across different product areas. We value not only technical know-how, but also creativity, user empathy, and teamwork.

You'll be a machine learning engineer in the Data org, contributing to diverse, high-impact machine learning challenges. In this role, you'll focus on designing, building, and deploying scalable ML solutions and systems within the credit environment. You'll lead experimentation with new modeling approaches and strategies, collaborate closely with engineers on ingesting signals and productionizing models, and help build the next wave of cash flow based underwriting. You'll own AI and machine learning work across the full model lifecycle, from offline training to online serving and monitoring, while helping define the ML roadmap with cross-functional teams.
Responsibilities
  • Build machine learning systems that empower millions of users through well-known and emerging fintech applications with access to financial services
  • Experiment with cutting-edge machine learning modeling techniques across high-impact credit use cases
  • Work on both 0-1 stage problems and scaling systems from 1-10
  • Develop AI and machine learning models across the full lifecycle, from offline training to online serving and monitoring
  • Design, build, and deploy scalable ML solutions and systems in a production environment
  • Collaborate with teams across Plaid to define the machine learning roadmap
  • Dive deep into data and apply data-driven decision-making in day-to-day work
  • Operate with high ownership on a bottom-up driven team
Qualifications
  • 6+ years of experience training and serving AI and machine learning models in a production environment
  • Experience in fintech lending, with a strong understanding of how models are built in that space
  • Experience building or working with data-intensive backend applications in large distributed systems
  • Ability to code and iterate independently using tools such as Python, Spark, Jupyter notebooks, and standard machine learning libraries
  • Strong ownership mindset and a track record of driving projects to business impact
  • Ability to work effectively with both technical and non-technical teams
  • Master's degree or equivalent work experience in Computer Science, Mathematics, Engineering, or a closely related field
  • Nice to have: data analytics and data engineering experience


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!

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.

About Plaid

Plaid is a financial services company based in New York City. The company builds a technology platform, which enables applications to connect with users' bank accounts. Plaid focuses on enabling consumers and businesses to interact with their bank accounts, check balances, and make payments through financial technology applications. The company was founded in 2013 by Zach Perret and William Hockey. In January 2020, Visa announced that it would acquire Plaid for $5.3 billion. The acquisition was completed in January 2021.
Learn more about Plaid
Size
600 employees
Industry
Founded
2011

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