Staff Machine Learning Engineer, Empower Finance

MLOps

Salary not provided

+ Equity

AWS

Kubernetes

Airflow

Terraform

Jenkins

Azure

Kubeflow

Mid and Senior level

Remote in US

More information about location

Credit health & financial management app

Open for applications

Credit health & financial management app

101-200 employees

FintechB2CCredit ScoringBankingPersonal financeMobileD2C

Open for applications

Salary not provided

+ Equity

AWS

Kubernetes

Airflow

Terraform

Jenkins

Azure

Kubeflow

Mid and Senior level

Remote in US

More information about location

101-200 employees

FintechB2CCredit ScoringBankingPersonal financeMobileD2C

Company mission

To expand access to fair credit to give anyone in the world the opportunity to improve their financial security and mobility.

Job

Company

Role

Who you are

3+ years of experience in MLOps, ML Engineering, or DevOps for machine learning
Experience with machine learning algorithms and model development process
Strong expertise in cloud platforms (AWS or Azure) for ML deployment
Experience with CI/CD pipelines (e.g., GitHub Actions, Jenkins) for ML
Strong knowledge of model monitoring tools (e.g., Evidently AI, MLflow)
Hands-on experience with orchestration frameworks (e.g., Airflow, Kubeflow)
Familiarity with Pyspark and Databricks is a plus
Familiarity with infrastructure-as-code (Terraform, CloudFormation) is a plus

What the job involves

As our first Machine Learning Engineer focusing on MLOps, you will play a pivotal role in operationalizing our ML models, ensuring they are scalable, reliable, and easy to monitor
You’ll work closely with our data scientists, server engineers, and infrastructure teams to build feature stores for model development, facilitate model refit/retrain iterations, enhance model deployment (CI/CD) pipeline, as well as strengthen model monitoring
Design and Implement Scalable MLOps Infrastructure: Develop and maintain the infrastructure required for the entire machine learning lifecycle, from data ingestion and model training to deployment and monitoring
Build and Maintain Feature Stores: Design and implement robust feature stores to ensure consistent and efficient feature management across all ML models
Automate ML Workflows: Develop and implement CI/CD pipelines for machine learning models, automating the deployment and monitoring process
Implement Resource Management and Orchestration: Utilize tools like Kubernetes, Airflow, or similar technologies to effectively manage and orchestrate ML resources
Monitor and Debug Production ML Systems: Establish comprehensive monitoring and alerting systems to ensure the health and performance of deployed ML models
Collaborate with Data Scientists and Server Engineers: Work closely with data scientists and server engineers to understand their infrastructure needs and provide effective solutions

Our take

An individual’s credit score greatly influences their life, affecting their ability to rent, receive loans, buy a house, and access affordable interest rates. But you have to have credit to build credit, leaving a lot of people in a catch-22 situation. Empower is a mobile-only app that makes credit more inclusive and accessible, helping customers achieve their credit health goals regardless of their credit history (or lack thereof).

Though other FinTech companies such as Mint or Personal Capital also offer impressive financial tracking for their customers, Empower’s comprehensive set of personal finance features including cash advance and automatic savings offerings make it a better choice for people who want to use a single app to manage their finances.

By empowering people to take control of their money through its range of financial services, Empower is working to break the cycle of paycheck-to-paycheck living. Backed by Blisce, Defy Ventures and Quiet Capital, the company has been significantly growing its revenue in recent years and was recognized in the 2022 Inc. 5000 list of the fastest-growing companies in the US.

Freddie

Company Specialist at Welcome to the Jungle

Insights

Top investors

45% employee growth in 12 months

Trustpilot (1.9)

Company

Funding (last 2 of 3 rounds)

Sep 2022

$75m

LATE VC

Mar 2020

$20m

SERIES A

Total funding: $99.5m

Company benefits

Generous equity package
Full healthcare benefits
Unlimited personal vacation
Technology expense reimbursement
Work from anywhere

Company HQ

Mission District, San Francisco, CA

Leadership

Warren Hogarth

(CEO)

Previous Partner at Sequoia Capital and is an Early Investor/Company Builder for multiple companies.

Justin Ammerlaan

(CTO)

Founder of Ammerlaan Initiatives and Co-Founder of White Room Trading. Previously worked as a Senior Software Engineer at SDM and a Technical Architect at Fujitsu.

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