Job Title : ML Engineer with AIOps exp
Location : Remote
Duration: 6+ Months
Bill Rate: $70/Hr
Job Type:w2 Contract
Client : Client to be discussed later
Work Authorization : US-Citizen, H-1B, OPT-EAD, GC-EAD
Job Description:
Design and evolve the Lakehouse schema (Delta Lake / Apache Iceberg) for multi-domain observability data at petabyte scale.
Implement dbt transformation models to generate mart-ready, denormalized fact and dimension tables.
Design, train, and deploy machine learning models for streaming multivariate anomaly detection, root-cause analysis, and incident forecasting.
Build low-latency streaming inference pipelines (Flink / Spark Streaming) for real-time anomaly scoring on APM, infrastructure, and security signals.
Design and operate the end-to-end AIOps workflow, spanning signal ingestion, feature computation, model inference, alert routing, and auto-remediation hooks.
Integrate AIOps insights with incident management platforms (PagerDuty, Opsgenie) and internal runbooks to deliver enriched, noise-reduced alerting.
Mentor junior ML and data engineers and conduct rigorous design reviews for new mart schemas and model architectures.
Require Skills:
Kafka + Streaming (Flink/Spark)
Lakehouse (Delta / Iceberg)
ML (Anomaly detection + time-series)
Observability (OTel, APM, Logs)
MLOps (feature store, drift, retraining)
SQL + Python (strong)
Equal opportunity Employer : We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.
Never miss an opportunity! Create an alert based on the job you applied for.
