Job Title

JD: Senior Machine Learning Engineer (Forecasting & Pricing Systems)Blue Enigma – Senior ML Engineer (AI Demand Forecasting + Dynamic Pricing)Location: Hybrid (Noida, India)Experience: 4–8 YearsCompensation: Competitive + ESOP for high performersCompany DescriptionBlue Enigma is a deep-tech product company operating in stealth, building modern systems for hospitality, AI automation, and large-scale property management.We are developing:- A next-generation PMS + CMS platform - AI demand forecasting system - AI-driven dynamic pricing engine - High-scale microservices powering real-time decision-makingYou will be the core ML expert responsible for building our entire AI intelligence layer from scratch.Role: Senior ML Engineer (Time-Series + Pricing Models)We are hiring a hands-on Senior ML Engineer who can design forecasting models, build pricing logic, engineer data pipelines, and deploy ML systems into production.You will own end-to-end:- Forecasting models - Pricing engine - Data pipelines - Model deployment - Real-time inference APIsThis role blends ML + MLOps + software engineering.Responsibilities1. Build Demand Forecasting Models- Develop models to predict occupancy, demand, pickup rate - Use time-series, boosting models, or deep learning - Capture seasonality, events, market trends - Evaluate and improve models continuously2. Build Dynamic Pricing Algorithms- Convert forecasts into revenue-optimized price recommendations - Implement elasticity-based models - Incorporate constraints (inventory, cancellation patterns) - Ensure pricing stability + explainability3. Data Engineering- Design data pipelines to ingest PMS booking data - Clean, transform, and generate ML features - Build automated workflows for daily retraining4. MLOps- Deploy models using Docker / Kubernetes / cloud services - Set up monitoring, logging, versioning - Implement drift detection & auto-retraining5. Collaboration With Backend Team- Work with backend engineers to expose ML models as APIs - Support real-time inference pipelines - Ensure low-latency response times6. Documentation + Ownership- Own architecture diagrams, reports, experiments - Communicate findings to product & engineering teamsRequired SkillsMust Have- 4–8 years experience as ML Engineer / Applied Scientist - Strong understanding of time-series forecasting - Experience with pricing / optimization / demand models - Strong Python engineering skills (not just Jupyter notebooks) - Deep experience with libraries: scikit-learn, Prophet, XGBoost, LightGBM, statsmodels - Experience deploying ML models into production - Strong understanding of MLOps (CI/CD, model versioning, monitoring) - Experience with SQL & NoSQL databases - Experience designing and consuming APIsNice to Have- Experience in hospitality, travel-tech, airline pricing, or e-commerce pricing - Experience with real-time inference systems - Knowledge of AWS/GCP (Lambda, ECS, S3, BigQuery, etc.) - Familiarity with deep learning time-series models (LSTM/Transformer-TS) - Prior experience building forecasting systems at scaleWhat We Offer- Build the AI brain of a global PMS platform - Ownership of ML architecture end-to-end - Competitive salary + ESOP opportunities - Freedom to innovate and ship fast - Work with a highly skilled engineering team - Opportunity to impact revenue optimization for 1000s of propertiesHow to ApplySend your:- Resume - GitHub / Kaggle / Project links - Any ML system architecture or relevant case studiesOr message us directly on LinkedIn.