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, Salt Lake City, Washington D.C., London and Amsterdam. #LI-Remote
Plaid’s Machine Learning 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 -- toward different product areas. We value not only technical know-how, but also creativity, user empathy, and teamwork.
You’ll be a machine learning engineer embedded on the Traffic team, working on the traffic scheduling problem. Specifically, you will focus on designing metrics customized for product optimization, building and deploying scalable ML or optimization system. You will lead the efforts to experiment with new modeling approaches and strategies, as well as collaborating closely with a skilled team of engineers on ingesting signals and productionizing these models. If you’re interested in building the state of art ML or optimization solutions to unblock financial freedom for everyone, let’s chat! We’re guided by our principles including impact, growing together, embracing openness and positivity, and inventing tomorrow. We’re looking for leaders who are motivated by those same principles!
What excites you
- Build with impact. Your work will empower millions of users through well-known and emerging Fintech Applications with access to financial services.
- Apply ML and optimization technique to real world financial data traffic problems under various scenarios.
- Work on both 0-1 stage problems as well as 1-10.
- Develop ML and optimization models in a full lifecycle, from offline training to online serving and monitoring.
- Collaborate with teams across Plaid to define ML roadmap.
- Dive deep into data and apply data driven decisions in day-to-day work.
- A high ownership, bottom-up driven team.
What excites us
- 5+ years in training and serving ML and optimization models in a production environment.
- 3+ years in building data intensive backend applications in large distributed systems.
- Ability to code and iterate independently on top of data infrastructure tools like Python, Spark, Jupyter notebooks, standard ML libraries, etc.
- Take pride in taking ownership and driving projects to business impact.
- Experience with industry application of optimization (integer programming, multistage stochastic optimization, approximate dynamic programming etc.) and/or reinforcement learning is a big plus.
- Data analytics and data engineering experience is a plus.
- Ability to work with technical and non-technical teams.
- Master’s degree or equivalent work experience in Computer Science, Mathematics, Engineering, Operation Research, or a closely related field.
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
[email protected].
Please review our Candidate Privacy Notice
here.
