Skill- AIML Engineer
Total Experience-3-7yrs
Mode - Hybrid
JD:
Key Responsibilities:
AI Ops & Observability
· Design, implement, and operate AI‐driven monitoring and observability solutions across application, infrastructure, and network layers.
· Able to build AI‐based anomaly detection for metrics such as traffic patterns, error rates, latency, and infrastructure capacity.
· Integrate observability platforms such as Dynatrace, Splunk, Open Telemetry, and custom metrics pipelines for AI monitoring and insights.
· AI‐enabled alert reduction and error detection
Automation & Intelligent Operations
·Develop AI‐powered automation to reduce operational toil, manual triage, and repetitive tasks.
· Implement alert reduction, intelligent correlation, and RCA automation for production incidents.
·Enable self‐healing and auto‐remediation workflows where applicable.
Required Skills:
·5+ years of experience in Python using common data science libraries such as scikit-learn and Databricks.
· 3+ years of experience applying NLP (transformers, gpt,etc)



in a production setting using large amounts of data.
· 2-3 years of experience applying LLMs (RAG, vector db, embeddings) to solve real world problems.
· Experience applying data science techniques in a commercial enterprise, including supervised, unsupervised learning, NLP, time-series forecasting and other statistical analyses.
· Experience building APIs for the models.
· Good experience with one of the cloud platforms (Azure, AWS or GCP). Having Azure cloud experience is more preferred.
·Solid written & verbal communication skills; including the ability to present detailed analyses to a broad audience.
· Organized self-starter, with drive and commitment; able to work with little supervision.
· Analytical, quantitative, problem-solving, and critical thinking skills
Nice-to-Have:
· Experience using vision and speech models in Gen AI
· Experience with AI/ML concepts applied to operations
· Knowledge of SRE practices, incident manag

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