ROLE OVERVIEW

We are seeking a hands-on, highly experienced, production-focussed ML engineer to design, develop and productionise several ML use cases for the rental real estate sector in UK and Europe. Specific use cases include dynamic pricing models, recommendation engines (e-commerce type) for dynamic, personalised recommendations and offers and prediction models for rent and occupancy forecasting. This is a founding senior hire at the GCC inception stage with a clear career path to fast-tracked team leadership.

KEY RESPONSIBILITIES

ML Development & Deployment

- Design, develop and deploy production-grade ML models for dynamic pricing, personalised price and product recommendation engines, automated property valuation, rent and occupancy prediction models, sentiment evaluation
- Develop algorithms to analyse pricing anomalies and respond to real-time supply-demand data and create an impact on revenue management
- Identify micro-location factors driving rental growth and build models for automated price setting
- Develop computer vision models for property image analysis, floor plan processing, and automated condition assessment

MLOps & Infrastructure

- Build robust MLOps pipelines model training, versioning, CI/CD, monitoring, and drift detection
- Implement model monitoring for performance degradation and data quality issues
- Optimise model performance for latency, throughput, and cost efficiency in production




- Collaborate closely with UK and Europe teams to translate business problems into ML solutions

REQUIRED TECHNICAL SKILLS

Python

Expert-level; production-quality code; strong software engineering fundamentals

ML Frameworks

Deep expertise in PyTorch or TensorFlow; hands-on proficiency in scikit-learn, XGBoost, LightGBM

AI for model fine-tuning

Exposure to an AI-enabled environment for model buildingand fine-tuning

MLOps

MLflow or Weights & Biases; model versioning, A/B testing, drift monitoring in production

Cloud

Proficiency on any major cloud platform (AWS, Azure, or GCP) for ML deployment

Containerisation

Docker and Kubernetes for model deployment and CI/CD pipelines

Dynamic Pricing

Proven capability in building energetic pricing models eg in e-commerce, retail, travel, hospitality, financial products

IDEAL CANDIDATE PROFILE

- 3+ years deploying ML models in live production environments (not just training or PoC)
- Track record of model serving at 10,000+ predictions/day with sub-100ms latency
- Proven ability in building dynamic pricing models or recommendation engines is a pre-requisite
- Experience in NLP/Document AI, Computer Vision, Time Series and trend Forecasting
- Background in finance, retail or e-commerce domains is a strong advantage
- Interest in playing a leadership role and mentoring junior team members as the team grows.

📌 Machine Learning Engineer (Bengaluru)
🏢 V3 Staffing
📍 Bengaluru