Job Description
Hi,
Looking for candidates with strong experience in Machine Learning, Python, GCP, Pricing models, LLM/RAG and MLOPS.
Interested candidates can share their updated CV at sa********n@v3*******g.in
Experience: 5 to 8 years
Notice period: immediate to 30 days
Education: B.E/B.Tech or M.Sc/MCA/M.Tech
Please find the JD below:
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
Job Classification
Industry: Software Product
Functional Area / Department: Data Science & Analytics
Role Category: Data Science & Analytics - Other
Role: Data Science & Analytics - Other
Employement Type: Full time
Contact Details:
Company: Top product-based
Location(s): Bengaluru
Keyskills:
Machine Learning
GCP
Pricing
Mlops
Python
Tensorflow
scikit-learn
LightGBM
ai
LLM
Pytorch
Docker
XGBoost
RAG
Kubernetes