Senior ML Engineer - Remote, Production Monitoring Lead

Candid; United States; Hybrid; USD 130,000 - 160,000; Full time

Benefits offered by this job

Health insurance

Retirement contribution with match

Paid leave time (PTO, holidays, etc)

Disability insurance

Pre-tax transit benefits

PSLF program eligible employer

Job summary

Candid, a nonprofit, is seeking a Senior Machine Learning Engineer to own deployed ML services, monitor them in production, and improve deployment and observability. You will work with data scientists and engineers to scale and productionize models, while keeping cost-conscious practices in mind.

You will design CI/CD for ML, manage experiments and model artifacts, and help ensure reliable, scalable services on AWS. Remote role with periodic in-person leadership meetings.

Qualifications

• 4+ years of professional software engineering with production ML systems.
• Strong Python production-quality service code experience.
• Experience deploying ML models in production and monitoring reliability.

Responsibilities

• Own deployed ML/AI services, monitor degradation and retraining cadences.
• Improve inference performance with quantization, batching, and efficient serialization.
• Design and operate experiment tracking, model versioning, and artifact management.
• Build observability: logging, metrics, dashboards, and alerting.
• Establish repeatable deployment paths for new ML services on AWS with CI/CD.
• Monitor AWS spend and publish cost visibility to the team.
• Translate research code to production deployments and work with cross-functional teams.

Skills

Python proficiency

Team collaboration

Problem solving

Verbal communication

Tools

MLflow

Weights & Biases

ONNX Runtime

AWS Lambda

ECS/Fargate

S3

CloudWatch

Bedrock

Job description

Candid, a nonprofit, is seeking a Senior Machine Learning Engineer to own deployed ML services, monitor them in production, and improve deployment and observability. You will work with data scientists and engineers to scale and productionize models, while keeping cost-conscious practices in mind.

You will design CI/CD for ML, manage experiments and model artifacts, and help ensure reliable, scalable services on AWS. Remote role with periodic in-person leadership meetings.