Machine Learning Engineer / Data Scientist

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