Job description

**Skills:** Data Science, Machine Learning, PYTHON, GEN AI, NLP, MLOPS, Job Title: Machine Learning Engineer / Data Scientist Role Summary We are seeking a strong Machine Learning Engineer \+ Data Scientist hybrid to design, build, and productionize ML\-driven observability solutions on top of large\-scale session data (RUM, logs, WebRTC, clickstreams). The role focuses on behavioral inference, anomaly detection, multimodal signal fusion, and scalable ML systems to reduce MTTR/MTTD and improve user experience insights. **Required Skills** Core ML \& DS **Strong Foundation In:** * Supervised \& unsupervised learning * Anomaly detection * Time\-series modeling (Prophet/ARIMA/Deep Learning) * NLP (Transformers, BERT variants) * GenAI \- LLM, RAG, Agentic Experience with multimodal ML systems Engineering \& Systems Strong Python skills **Experience With:** * PySpark / Spark / distributed data processing * Streaming systems (Kafka) * APIs \& microservices Ability to handle high\-scale event data pipelines Modeling Techniques Clustering ( hierarchical, KMeans, density\-based) Classification (XGBoost, tree\-based models) Feature extraction (TF\-IDF, embeddings) MLOps \& Deployment **Experience With:** * ML pipelines (Airflow, Kubeflow, etc.) * Docker/Kubernetes * Model versioning \& monitoring Good to Have Experience with observability/RUM tools Knowledge of WebRTC/audio signal processing Exposure to LLMs, RAG, and prompt engineering Understanding of frontend performance metrics (LCP, INP, CLS) **Experience** 6\+ years in Data Science / Machine Learning Engineering roles Prior experience in production ML systems is mandatory