Truebill is a fast-growing, product-focused company with the mission of meaningfully improving the financial health of millions of people. We do this by building easy-to-use interfaces for understanding personal finances, providing valuable insights into how our users can better save for the future, and cancelling or negotiating recurring subscriptions and bills that users are spending too much on.

Truebill is looking for a Machine Learning (ML) Ops Engineer to help us design, build and scale our data and machine learning infrastructure. This role will work closely with data science, engineering, and product to ensure that we're delivering reliable and accurate data to our users who depend on Truebill to navigate their financial lives. You'll have the opportunity to work on projects which can meaningfully improve the financial health of millions of people, and grow alongside a team of experienced builders as you do it.

About Truebill Engineering:

  • We are user focused. As we build software, we keep the end-user in mind to ensure that we're building something that will make a difference for them.
  • We are all both students and teachers. We value the sharing of knowledge and the drive to grow and become better engineers, data scientists, product managers, and more

About the role:

  • Work with the data science and engineering team to improve and generalize our existing production model pipelines. (Should we use Kubeflow? PySpark? Help us decide!)
  • Help us understand the buy vs. build tradeoffs and be a key stakeholder in delivering quality data and predictions to our users.
  • Define and implement engineering best practices for our ML infrastructure, such as unit testing, data validation and CI / CD.
  • Create scalable and friendly processes for efficient monitoring, tracing, profiling, and debugging.
  • Work closely with the data science team and product owners to continuously evaluate production models.
  • Take full ownership and responsibility for building, shipping, and maintaining core data infrastructure.

About you:

  • Practical experience serving predictions at scale - from model training and versioning to observability and delivery to consumers.
  • Exposure to machine learning concepts (feature engineering, text classification and time series prediction) and interest in learning more.
  • Operational experience with machine learning libraries and frameworks such as scikit-learn, Keras, or MLLib.
  • 3+ years experience deploying robust APIs in production environments (ideally cloud-based environments such as GCP or AWS).
  • (Nice to have) Experience deploying machine learning models using cloud based solutions such as Sagemaker, Azure ML.
  • (Nice to have) Production experience with serverless platforms such as Google Cloud Functions or AWS Lambda.
  • (Nice to have) Familiarity with and ability to train people on deploying to a Dockerized environment.

We offer:

  • Health, Dental & Vision Plans
  • Competitive Pay
  • Equity
  • Matching 401k
  • Unlimited PTO & Sick

 

Truebill, Inc. is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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