Role overview
About Payscale
Payscale is the original compensation innovator for organizations who want to scale their business with pay and transform their largest investment into their greatest advantage. With decades of innovation in sourcing reputable data and developing AI-powered tools, Payscale delivers actionable insights that turn pay from a cost to a catalyst. Its suite of solutions — Payfactors, Marketpay, and Paycycle — empower 65% of the top companies in the U.S. and businesses like Panasonic, ZoomInfo, Chipotle, Quest Diagnostics, University of Washington, American Airlines, and TJX Companies.
Create confidence in your compensation. Payscale.
To learn more, visit www.payscale.com.
Job Summary
We’re looking for an early-career Machine Learning Engineer to help take models built by our Data Science team and turn them into reliable, production-ready services. As a member of our Data Engineering team, you will play a critical role in reviewing, optimizing, and deploying AI/ML models into production environments. You’ll work alongside experienced engineers and data scientists, contributing to model packaging, training, deployment, integration, testing, and monitoring—while growing your MLOps and software engineering skills.
What you'll work on
- Partner with Data Science to package models for deployment and integrate them into our products and internal services.
- Implement and improve ML deployment and inference workflows (batch and/or real-time), including automation and CI/CD patterns with guidance from senior engineers.
- Build and maintain API endpoints or services that expose model predictions, including input validation, error handling, and documentation.
- Write tests (unit/performance/integration) to validate model behavior and service reliability; help create repeatable validation checks and release processes.
- Instrument services with logging/metrics and help monitor production behavior; participate in incident triage and troubleshooting with support from the team.
- Contribute to performance and cost improvements through profiling and practical techniques like batching, basic caching, and efficiency-minded design.
- Stay current on relevant AI/ML engineering best practices and share learnings with the team.
What we're looking for
- Exposure to MLOps tools or patterns (e.g., MLflow, Airflow, Kubeflow, feature stores, model registries).
- Experience with containers (Docker) and/or orchestration (Kubernetes).
- Experience with observability tools (e.g., Datadog, Prometheus/Grafana) and production troubleshooting.
- Basic performance tuning experience (profiling, async patterns, caching concepts).
- Experience working with data platforms (e.g., Snowflake, Spark) or large-scale data pipelines.
Location
Payscale has an employee centric remote-first model that provides you the flexibility to do your best work in a space that supports you, while also finding time to collaborate in person for the moments that matter.
In our remote-first model, employees can work from the location that works best for them. We do not have centralized corporate offices. Employees can choose to work from home, in company-paid co-working spaces, or any combination of the two that best suits their unique needs.
If you work from home, we recommend ensuring that you can meet the following technology, equipment and workspace requirements:
- High-Speed Internet - A stable broadband or fiber connection (satellite is highly discouraged) with a minimum speed of 100 Mbps in a dedicated workspace that has a reliable Wi-Fi signal.
- Device for Multifactor Authentication (MFA/2FA) - smartphone, tablet, etc.
When it matters (usually no more than a few times a year) we take the time to gather for in-person events.
Payscale has employees across the US, Canada, UK, The Philippines and Romania however we are currently unable to hire in the Quebec Province, Northern Ireland, and Hawaii.
Benefits And Perks
All around awesome culture where together we strive to live our 5 values:
- Data informed decision making.
- Customer first. Always.
- Succeed together.
- Relentless about results. Obsessed with excellence.
- Lead the change. Shape the standard.
An open and inclusive environment where you’ll learn and grow through programs and resources like:
- Monthly company All Hands meetings
- Regular opportunities for executive leadership exposure through things like AMAs
- Access to continued learning & development opportunities
- Our commitment to a continuous feedback culture which allows us to drive performance and career growth
- A growing network of Employee Resource Groups
- Company sponsored volunteer hours
- And more!