MLOps Engineer
Redolent
MLOps Engineer
Duration: 12+ Months Location: Sunnyvale CA - hybrid Rate: DOE
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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