Senior Machine Learning Engineer

JD: Senior Machine Learning Engineer (Forecasting & Pricing Systems)

Blue Enigma Senior ML Engineer (AI Demand Forecasting + Dynamic Pricing)

Location: Hybrid (Noida, India)

Experience: 48 Years

Compensation: Competitive + ESOP for high performers

Company Description

Blue 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-making

You 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 APIs

This role blends ML + MLOps + software engineering.

Responsibilities

1. 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 continuously

2. Build Dynamic Pricing Algorithms

• Convert forecasts into revenue-optimized price recommendations
• Implement elasticity-based models
• Incorporate constraints (inventory, cancellation patterns)
• Ensure pricing stability + explainability

3. Data Engineering

• Design data pipelines to ingest PMS booking data
• Clean, transform, and generate ML features
• Build automated workflows for daily retraining

4. MLOps

• Deploy models using Docker / Kubernetes / cloud services
• Set up monitoring, logging, versioning
• Implement drift detection & auto-retraining

5. Collaboration With Backend Team

• Work with backend engineers to expose ML models as APIs
• Support real-time inference pipelines
• Ensure low-latency response times

6. Documentation + Ownership

• Own architecture diagrams, reports, experiments
• Communicate findings to product & engineering teams

Required Skills

Must Have

• 48 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 APIs

Nice 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 scale

What 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 properties

How to Apply

Send your:

• Resume
• GitHub / Kaggle / Project links
• Any ML system architecture or relevant case studies

Or message us directly on LinkedIn.