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MLOps Engineer

Redolent

Role: MLOps Engineer


Duration: 12+ Months


Location:Sunnyvale CA - hybrid


Rate: DOE

Job Description:

Key Responsibilities : Design and implement scalable model serving platforms for both batch and real-time inference Build model deployment pipelines with automated testing and validation Develop monitoring, logging, and alerting systems for ML services Create infrastructure for A/B testing and model experimentation Implement model versioning and rollback capabilities Design efficient scaling and load balancing strategies for ML workloads Collaborate with data scientists to optimize model serving performance


Technical Requirements :


7+ years of software engineering experience, with 3+ years in ML serving/infrastructure Strong expertise in container orchestration (Kubernetes) and cloud platforms


Experience with model serving technologies (TensorFlow Serving, Triton, KServe) Deep knowledge of distributed systems and microservices architecture


Proficiency in Java or Python and experience with high-performance serving


Strong background in monitoring and observability tools


Experience with CI/CD pipelines and GitOps workflows
Vacancy posted 4 days ago
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