Senior MLOps / AI Ops Engineer
$120,000–$160,000 year
Remote · New York City, New York, United States or US
Job Summary
Design, implement, and optimize MLOps/AI Ops architectures for scalable AI/ML solutions. Build and manage cloud-native infrastructure using Azure, Kubernetes, Docker, and Terraform. Lead end-to-end AI/ML lifecycle operations, focusing on data ingestion, model training, deployment, and monitoring. Drive AI Ops capabilities such as prompt lifecycle management and semantic search enhancements. Collaborate with data engineering teams to ensure efficient data pipelines, while maintaining security and governance in ML/AI systems. Ideal candidates will have over 12 years of experience with strong skills in MLOps and AI Ops.
Required Qualifications
- 12+ years of overall experience
- Strong expertise in MLOps, AI Ops, and cloud infrastructure
- Hands-on experience with Kubernetes, Docker, Terraform, Azure cloud, and CI/CD pipelines
- Strong understanding of the full AI/ML lifecycle
- Experience with LLM lifecycle, prompt management, and semantic caching
- Solid understanding of infrastructure-as-code and cloud-native architectures
- Knowledge of IAM, secrets management, and compliance frameworks
- Proven ability in performance tuning and managing large-scale distributed systems
- Excellent communication and leadership skills.
Desired Qualifications
- Experience with reliability engineering, SRE practices, and cost-optimization strategies.
- Exposure to monitoring tools and frameworks for AI/ML observability.
- Certifications in Azure, Kubernetes, DevOps, or AI/ML.
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