Note: The job is a remote job and is open to candidates in USA. Payscale is a compensation innovator that helps organizations scale their business with pay. They are looking for an early-career Machine Learning Engineer to help turn models into reliable, production-ready services, working closely with the Data Engineering team.
Responsibilities
- 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
Skills
- Bachelor's or master's degree in Computer Science, Engineering, or related field
- 1+ years of experience (including internships/co-ops) building software in a production environment
- Proficiency in Python with a focus on readable, testable code
- Familiarity with core ML concepts and at least one ML framework (e.g., PyTorch, TensorFlow, scikit-learn)
- Familiarity with building or consuming APIs (HTTP/JSON) and basic service development patterns
- Comfort working in a collaborative environment: asking questions, communicating tradeoffs, and incorporating feedback
- Willingness to learn cloud, containerization, and MLOps practices as part of day-to-day work
- 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
Benefits
- Flexible paid time off, giving you the opportunity to rest, relax and recharge away from work
- 14 Paid Company Holidays, includes 2 floating holidays (you choose!)
- A comprehensive benefits plan including medical, dental, life, vision, disability, and life insurance covered up to 100% by Payscale
- Unlimited infertility coverage benefits through our medical plans
- Additional supplemental health benefits offered to you and your family
- 401(k) retirement program with a fully vested immediate company match
- 16 weeks of paid parental leave for birthing and non-birthing parents
- Health Savings Account (HSA) options and company contributions each pay period
- Flexible Spending Account (FSA) options for pre-tax employee allocations
- Annual remote work stipend to be used on wellness or home office equipment
Company Overview
Payscale provides compensation software, data and services to employers and free salary information and negotiation resources to individuals It was founded in 2002, and is headquartered in Seattle, Washington, USA, with a workforce of 501-1000 employees. Its website is https://www.payscale.com.
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