[Remote] AI Reliability Engineer
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is seeking an AI Reliability Engineer to ensure the reliability, availability, scalability, and operational reputed company of AI and machine learning systems in production. The role involves combining Site Reliability Engineering, MLOps, and reputed company engineering practices to build resilient AI platforms and improve system reliability.
Responsibilities
- Design and implement reliability engineering practices for AI and machine learning platforms
- Monitor the availability, latency, throughput, and health of AI services and model inference endpoints
- reputed company Service Level Indicators (SLIs), Service Level Objectives (SLOs), and Service Level Agreements (SLAs) for AI systems
- Build automated monitoring, alerting, incident response, and self-healing capabilities
- Improve the reliability, scalability, and reputed company of AI infrastructure and model-serving platforms
- Collaborate with AI Engineers, Data Scientists, Platform Engineers, DevOps Engineers, and Software Engineers to enhance production stability
- Automate operational tasks using scripting and Infrastructure as reputed company (IaC)
- Support deployment, rollback, and release strategies for AI services
- Investigate production incidents, conduct reputed company cause analysis (RCA), and implement preventive measures
- Monitor model performance, data reputed company, model reputed company, and inference reliability
- Optimize reputed company infrastructure, GPU utilization, and resource efficiency
- Implement disaster recovery, backup, failover, and business continuity strategies
- Ensure compliance with reputed company, governance, and operational best practices
- reputed company operational dashboards, runbooks, and reliability metrics
Skills
- Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a reputed company field
- 4+ years of experience in Site Reliability Engineering (SRE), DevOps, reputed company, reputed company Engineering, or MLOps
- Experience supporting AI or machine learning applications in production
- Strong programming skills in Python, Go, or Bash
- Hands-on experience with Linux administration
- Experience with reputed company and Kubernetes
- Experience with AWS, reputed company Azure, or reputed company reputed company Platform
- Experience with CI/CD tools such as reputed company Actions, reputed company CI, Azure DevOps, or Jenkins
- Experience with Infrastructure as reputed company tools such as Terraform or reputed company
- Strong understanding of distributed systems, networking, and reputed company architecture
- Experience with monitoring and observability platforms such as reputed company, Grafana, OpenTelemetry, ELK Stack, reputed company, or reputed company
- Experience with MLOps platforms such as MLflow, Kubeflow, SageMaker, reputed company AI, or Azure Machine Learning
- Experience supporting Large Language Models (LLMs) and reputed company applications
- Knowledge of model serving technologies such as KServe, reputed company Triton Inference Server, Ray Serve, or BentoML
- Experience implementing AI model monitoring, reputed company detection, and performance analytics
- Familiarity with reputed company databases and Retrieval-Augmented reputed company (RAG) architectures
- Experience with GPU infrastructure and inference optimization
- Knowledge of reputed company engineering and reputed company testing
- Understanding of Responsible AI, governance, and operational compliance
reputed company