Machine Learning Engineer

Senior Operational Intelligence Engineer – AI Ops / Network TelemetryWork Model: 4 days onsite / 1 day remoteOverview A leading telecommunications organization is expanding its Operational Intelligence function to support the evolution of an AI-driven Network Operations platform . This platform continuously monitors large-scale network environments—processing tens of millions of telemetry records every five minutes —to detect anomalies, correlate signals, diagnose root causes, and enable automated or recommended corrective actions.The Senior Operational Intelligence Engineer will serve as a technical leader responsible for ingesting, enriching, and analyzing high-volume real-time telemetry across broadband, IP video, wireless, and core infrastructure environments.This role will focus on building scalable monitoring pipelines, driving anomaly detection strategies, troubleshooting complex network degradations, and contributing to the development of AI-driven and self-healing network operations systems .This is a senior-level engineering role suited for someone with deep experience in large-scale telemetry systems, Linux, Python, AWS, and distributed system troubleshooting .Key Responsibilities Lead ingestion, transformation, and correlation of massive real-time telemetry streamsDesign monitoring pipelines that surface early warning indicators and trigger automationDefine strategies for anomaly detection, fault identification, and system health monitoringInvestigate and troubleshoot high-impact network events across distributed systemsCorrelate signals across data domains to determine root cause and remediation actionsServe as a technical escalation point for complex production issuesBuild automation workflows that detect faults and drive operational responsesContribute to AI Ops and agentic AI initiatives by defining telemetry signals and data modelsArchitect and optimize data pipelines within AWS environmentsEvaluate and implement data streaming technologies such as Kafka, NiFi, Fluentd, or KinesisMentor junior engineers and support onboarding and technical developmentContribute to engineering documentation, runbooks, and operational best practicesRequired Qualifications 5–8+ years of experience in ML Ops, data engineering, or operational intelligence environmentsStrong experience working with telemetry systems and high-volume streaming dataExperience with real-time anomaly detection and large-scale data correlationAdvanced Python development for data processing, automation, and pipeline developmentStrong Linux expertise including debugging, log analysis, and performance troubleshootingExperience troubleshooting large distributed systems with thousands of endpointsAbility to design scalable data models and workflows for extremely large datasetsHands-on experience with AWS services such as SageMaker, Bedrock, Kinesis, EC2, or LambdaStrong analytical and problem-solving skills in mission-critical environmentsSoft Skills Strong communicator able to translate complex telemetry insights into actionable outcomesStrategic thinker who enjoys improving system reliability and automationPassion for data analysis, correlation, and operational intelligenceInterest in mentoring and guiding junior engineers#J-18808-Ljbffr