AI/MLOps Engineer
5 days ago
AI/ML Ops Engineer – AIOps, GenAI & Cloud
Experience: 4+ Years
Location: Remote (1–2 days/month from any HCL location)
Work Hours: 11:00 AM – 8:30 PM IST
Employment Type: Full-Time / Contract
About the Role:
We are seeking a skilled AI/ML Ops Engineer to design, develop, and deploy intelligent AIOps solutions that enhance IT system reliability and automate root cause analysis. The ideal candidate will have strong experience in building scalable ML pipelines, anomaly detection models, and operational automation using modern cloud and DevOps technologies.
Key Responsibilities:
Design, develop, and deploy AI/ML models for anomaly detection, predictive incident management, and automated root cause analysis in IT systems.
Integrate AIOps solutions with enterprise monitoring tools such as Splunk, Datadog, Prometheus, and AppDynamics.
Collaborate closely with SRE, DevOps, and IT operations teams to identify automation opportunities and operational efficiency improvements.
Build and maintain data pipelines to collect, process, and analyze logs, metrics, and events from diverse sources.
Apply NLP techniques for log analytics, intelligent alert correlation, and contextual insights.
Monitor and retrain ML models to ensure continuous performance optimization.
Contribute to the development of dashboards and visualization tools for real-time operational insights.
Support implementation of GenAI-based automation and integrate AI Python SDKs for intelligent workflows.
Required Qualifications & Skills:
Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
3+ years of hands-on experience in AI/ML engineering, ideally within IT operations, DevOps, or AIOps domains.
Proficiency in Python and popular ML libraries (TensorFlow, PyTorch, Scikit-learn, etc.).
Strong understanding of time-series analysis, anomaly detection, and predictive modeling.
Experience implementing and integrating GenAI and AI SDKs (e.g., OpenAI, Azure AI, LangChain, etc.).
Familiarity with cloud environments (AWS, Azure, or GCP) and containerized deployments (Docker, Kubernetes).
Experience in CI/CD pipelines and ML Ops workflows is highly desirable.
Knowledge of ITSM / ITIL processes and tools is a plus.
Nice to Have:
Experience with observability tools (Grafana, Elastic Stack).
Exposure to data engineering frameworks (Apache Kafka, Airflow).
Prior work in automation of incident resolution and self-healing systems.
Job Types: Full-time, Contractual / Temporary
Contract length: 6 months
Pay: ₹70, ₹80,000.00 per month
Experience:
- AI/ML: 4 years (Required)
- AIOps: 2 years (Required)
- GenAI & Cloud: 1 year (Required)
Work Location: Remote
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