Job Description
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
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