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Senior ML Ops Engineer
RemoteFull-timeAI & Machine LearningAdvertising
Join a growing performance marketing company as a hands-on ML Ops Engineer. Partner with data scientists and engineers to build reliable, reproducible, observable, and cost-efficient machine learning platforms and production systems. The role offers flexible remote work and direct impact on company,
Responsibilities
- Productionize batch and real-time model training and inference workflows
- Establish CI/CD, data versioning, model governance, and deployment practices
- Develop feature generation and feature store patterns, model registries, and metadata management
- Build monitoring, alerting, and dashboards for data quality, drift, model performance, latency, and pipeline health
- Refactor research code into reusable components with consistent repository structures, testing, logging, and reproducibility
- Collaborate with data scientists, analysts, and engineers to turn prototypes into production systems
- Provide mentorship and technical guidance across the engineering team
- Define the technical vision and architectural standards for ML platform capabilities
Requirements
- At least 5 years of ML Ops experience, including ownership of ML infrastructure for large-scale systems
- Strong Python software engineering experience, including automated pipelines that bring machine learning models into production
- Experience with coding, debugging, performance analysis, testing, CI/CD, and reproducible builds
- Production experience with AWS, Databricks, Docker, and Kubernetes, including EKS, ECS, or equivalent
- Experience using Terraform or CloudFormation to manage reviewable infrastructure environments
- Experience with MLflow, SageMaker, or comparable machine learning lifecycle tooling
- Experience implementing monitoring for data quality, model drift, model performance, latency, and pipeline health
- Strong communication and collaboration skills when working with data scientists, analysts, and engineers
Nice to have
- Experience with PySpark, AWS Glue, Dask, or Kafka
- Experience integrating third-party data
- Familiarity with real-time endpoints, batch scoring, and feature stores
- Exposure to model governance, compliance, and secure ML operations
Benefits
- Competitive compensation
- Flexible remote work
- Unlimited responsible PTO
- Opportunity to influence a growing, cash-flow-positive company