MLOPS Engineer - Remote
apolisDenver (CO)
About the role
Position: : MLOPS Engineer
Duration: : Long Term Contract
Role: : 100% Remote
Must haves: PYTHONGCPMLOPSEnterprise level Experience Individual Contributor
Job Description
Overview:
The Client is seeking experienced MLOps Engineers to support the productionization, scalability, and operational excellence of enterprise advertising technology solutions. These engineers will play a critical role in transforming proven machine learning capabilities into resilient, cost-effective, multi-tenant production platforms. This position focuses on deploying, monitoring, optimizing, and maintaining machine learning systems supporting search, recommendation, forecasting, advertising optimization, and advanced analytics use cases.
Key Responsibilities
Productionization & Deployment:
Deploy machine learning models into scalable production environments.
Build and maintain CI/CD pipelines for machine learning workloads.
Partner closely with Data Scientists to operationalize new models and capabilities.
Implement model serving and deployment strategies across multiple business units.
Platform Engineering:
Design and support scalable multi-tenant machine learning infrastructure.
Improve platform reliability, performance, and observability.
Develop reusable deployment frameworks and infrastructure templates.
Ensure platform consistency across multiple regions and business domains.
Operational Excellence:
Monitor model health, performance, data quality, and system reliability.
Establish alerting, logging, and automated remediation processes.
Optimize infrastructure utilization and cloud spend.
Troubleshoot production incidents and drive root-cause resolution.
Data & Pipeline Engineering:
Build and optimize batch and real-time ML pipelines.
Improve workflow orchestration and data movement processes.
Support feature engineering pipelines and model retraining frameworks.
Ensure reliability and scalability of production data infrastructure.
Required Qualifications:
- 5+ years of experience in MLOps, Machine Learning Engineering, Data Engineering, or Platform Engineering.
- Strong Python development experience.
- Experience deploying machine learning solutions in cloud environments.
- Hands-on expertise with:
- GCPDatabricksAirflowCI/CD pipelines
- Infrastructure automation
- Experience supporting production machine learning systems.
Preferred Qualifications:
Experience supporting search, recommendation, ranking, or advertising platforms.
Knowledge of model monitoring and observability frameworks.
Experience with cloud cost optimization and performance tuning.
Experience supporting multi-tenant platforms.
Familiarity with modern MLOps frameworks and deployment patterns.
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