Senior ML Engineer — Production AI & MLOps

Data; Northern (KY); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Candid is seeking a Senior ML Engineer to take operational ownership of deployed ML/AI services, ensuring reliable production performance and governance. You will partner with data scientists to translate research into scalable deployments, implement CI/CD for ML, and optimize AWS-based infrastructure for cost and reliability.

You will build observability dashboards, manage model versioning and artifact handling, and work closely with product and software engineering teams to define integration

Qualifications

• 4+ years of professional software engineering, with at least 2 years in production ML systems (MLOps or production ML focus).
• Strong Python production-quality service code.
• Hands-on experience with experiment tracking and model lifecycle tooling in production (MLflow, Weights & Biases).
• Experience deploying PyTorch models in production with optimization techniques (quantization, batching, ONNX Runtime).
• Experience deploying and monitoring ML models in production, understanding drift, retraining triggers, and artifact management.
• Familiarity with AWS ML deployment stack (Lambda, ECS/Fargate, S3, IAM, CloudWatch).
• Experience building or operating CI/CD pipelines for ML services.
• Proven track record of improving production reliability via observability and disciplined deployment.
• Ability to collaborate with data scientists and translate their outputs to production decisions.
• Strong written and verbal communication; comfortable working independently.

Responsibilities

• Take operational ownership of deployed ML/AI services, monitor for issues, retraining cadences, and handoffs from data scientists.
• Improve inference performance of deployed models, including complex graph inference, via quantization, batching, and efficient serialization.
• Design and operate experiment tracking, model versioning, and artifact management for low-friction handoffs.
• Build and maintain observability: logs, metrics, dashboards, alerts to reduce incidents through good deployment hygiene.
• Establish repeatable deployment paths for new ML services on AWS with CI/CD and infrastructure-as-code patterns.
• Monitor AWS spend for ML workloads and publish cost visibility to the team (Bedrock, S3 lifecycle, etc.).
• Collaborate with data scientists to translate research code into production-ready deployments and surface operational insights.
• Serve as liaison between Data Science and product/software engineering teams to define integration contracts and SLAs.

Skills

Python

MLOps

PyTorch

AWS

CI/CD

Observability

Communication

Cross-functional

Model lifecycle

MLflow

Tools

MLflow

Weights & Biases

ONNX Runtime

Lambda

ECS/Fargate

S3

IAM

CloudWatch

Job description

Candid is seeking a Senior ML Engineer to take operational ownership of deployed ML/AI services, ensuring reliable production performance and governance. You will partner with data scientists to translate research into scalable deployments, implement CI/CD for ML, and optimize AWS-based infrastructure for cost and reliability.

You will build observability dashboards, manage model versioning and artifact handling, and work closely with product and software engineering teams to define integration