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:

o Supervised & unsupervised learning

o Anomaly detection

o Time-series modeling (Prophet/ARIMA/Deep Learning)

o NLP (Transformers, BERT variants)

o GenAI – LLM, RAG, Agentic

● Experience with multimodal ML systems

Engineering & Systems

● Strong Python skills

● Experience with:

o PySpark / Spark / distributed data processing

o Streaming systems (Kafka)

o 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:

o ML pipelines (Airflow, Kubeflow, etc.)

o Docker/Kubernetes

o 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