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Senior Machine Learning Engineer

Employer
ingenium.agency
Location
San Francisco, CA
Closing date
Jan 16, 2022

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Sector
Science, Physical Sciences and Engineering
Organization Type
Corporate
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Job Description
As an experienced machine learning engineer, you would own the entire machine learning pipeline from data sourcing and training to model serving, helping us productionize findings from data science into real-world applications. Your primary responsibility will be to develop and maintain production-quality software to host machine learning and statistical models and make them available to our platform. You will also design and build model training, publishing, and analytics pipelines for a multitude of machine learning models. In addition, you will validate model integrity and monitor performance while providing data scientists with tooling to accelerate their iteration cycles.

Your activities would be:

- Feature engineering for machine learning

- Iterating on and experimenting with models

- Building and maintaining reliable predictive services

- Documenting your work clearly for others to follow

- Implementing analytics pipelines to assess model results

- Setting up data and cloud environments to make data science more efficient

- Quickly learning new tools

In the first 90 days you would:

- Develop pipelines to compute and store predicted lifetime value for any customer that has changed state recently.

- Build models to predict repayment rates on installment loans given a user's previous loan history

- Combine credit scores derived from disparate datasets into a single ensemble score that predicts whether a new customer will be a good long-term customer

WHAT WE ARE LOOKING FOR:

Are you a machine learning engineer ready to help us redefine credit for the 21st century? We are on a mission to leverage data from partners around the globe to perform credit scoring for 3 billion people. The opportunities for you to make an impact are limitless.

You should be a clear and concise communicator, with an ability to communicate ideas to a wide range of stakeholders both technical and non-technical. You appreciate hearing different points of view and wait to hear others point of view before offering your own. You have a pragmatic approach to building systems, see multiple ways of solving problems, and are able to discuss the tradeoffs of each solution. You are technology agnostic with broad depth and breadth of experience using many different technologies.

Ideally you have traveled extensively or have lived in a developing country. You are empathetic, self-aware and respect all cultures. You are fun and enlightening to work with, and you have a good work/life balance with hobbies and interests you are happy to share with others.

OUR TECH STACK

Our technology stack consists of modern tools; we are open to technologies and pick the right tool for the job:

- Python for Machine Learning e.g. (Scikit-learn and PyTorch)

- Python/Scala for data pipelines

- Scala/Java/Python for micro-services and APIs

- Swagger(OpenAPI) for API documentation

- Docker and Kubernetes to package and run services

- AWS for cloud infrastructure

- On-premise servers for data processing and extraction at our partners

Requirements

- Degree in a relevant technical field or equivalent experience

- 8+ years of software or data engineering experience

- 5+ years of work experience building and deploying production machine-learned models

- Ability to own and deliver on large, multi-faceted projects with little guidance

- Experience productionizing code models developed by data science teams

- Experience with frameworks for model serving (e.g., Sagemaker)

- Experience with modern machine learning frameworks like Scikit-learn, Torch or Tensorflow

- Understanding of statistical modeling

- Demonstrable history of building production-quality software infrastructure

- Experience developing microservices

- Experience building data pipelines

- Expert experience in Python

- Some experience in Java

Desirable

- Masters or PhD

- Background in data science

- Experience in classification, regression, clustering, and graph analysis

- Experience with customer behavior modeling

Benefits

- Medical/Dental/Vision - full coverage of health premiums, with 50% covered for spouse and dependents

- 401(k)

- 12-week maternity/paternity leave

- Unlimited PTO

- Monthly contribution for wellness related activities and programs

- A chance to be part of something that makes a significant difference in people's lives
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