Machine Learning Engineer - Pricing Models

Looking for candidates with strong experience in Machine Learning, Python, GCP, Pricing models, LLM/RAG and MLOPS.

Experience : 5 to 8 years

Notice period : immediate to 30 days

Education : B.E/B.Tech or M.Sc/MCA/M.Tech

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 dynamic 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

Education :

UG : B.Tech / B.E. in Any Specialization

PG : MCA in Any Specialization, MS/M.Sc(Science) in Any Specialization, M.Tech in Any Specialization