Machine learning Scientist II - Customer Tech

Wayfair; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Wayfair in Bengaluru seeks machine-learning scientists to design, implement, and productionize ML systems powering customer understanding and personalization, including embeddings, recommendations, and preference modeling.

You will partner with engineers, analysts and PMs to apply ML techniques that directly influence Wayfair's revenue, while maintaining a user-centric focus and scalable deployment practices.

Qualifications

• Bachelor's degree with 4-5 years of experience or Master's degree with 3-4 years in CS/Math/Stats.
• Proficiency in Python or another high-level programming language.
• Strong theoretical understanding and hands-on experience with ML algorithms.
• Classical ML and deep learning techniques across NLP, sequence modeling, RL, recommendations, clustering, time series.
• Experience with Python ML ecosystem (NumPy, scikit-learn, PyTorch, XGBoost, etc.).
• Strong written and verbal communication and bias towards simplicity and efficiency.
• Curiosity and enthusiasm for continuous learning.

Responsibilities

• Design, build, deploy and refine large-scale ML/AI models and systems.
• Collaborate across cross-functional teams to translate business problems into ML solutions.
• Work with infrastructure and ML platform teams to deploy scalable services.
• Build robust ML models that impact customer experience.
• Identify opportunities and ROI from data and model improvements.
• Maintain a customer-centric approach in solving problems.

Skills

Python

ML algorithms

NLP

Deep learning

Time series

PyTorch

XGBoost

Communication

Education

Bachelor's degree in CS/Math/Stats

Master's degree in CS/Math/Stats

Tools

NumPy

scikit-learn

PyTorch

XGBoost

Airflow

Kubeflow

Vertex AI / GCP

Docker

Kubernetes

Job description

Job Summary

We are looking for machine-learning scientists for research and development of the ML systems that power our Customer understanding and personalization systems - Customer embeddings, Recommendation systems, user interest prediction, generative recommendation systems, short term and long term customer preference identification. In this role, you ll partner with fellow scientists, engineers, analysts, and product managers to apply machine learning skills to directly impact Wayfair s revenue.

Responsibilities

• Design, build, deploy and refine large-scale machine learning/AI models and algorithmic decision-making systems that solve real-world problems for customers
• Work cross-functionally with engineers, analysts, product managers and commercial stakeholders to understand business problems, opportunities and develop appropriately scoped ML solutions
• Collaborate closely with various infrastructure, and ML platform teams to develop production grade services that follow best-practices in how we build and deploy scalable ML services
• Build cutting edge robust ML models and systems that directly impact our customers every day
• Identify new opportunities and insights from the data (where can the models be improved what is the projected ROI of a proposed modification)
• Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on

What you ll need

• Bachelors degree with 4-5 years of experience or Master s degree with 3-4 years of experience in Computer Science, Mathematics, Statistics, or related field
• Proficiency in Python or one other high-level programming language.
• A strong theoretical understanding and solid hands-on experience working with machine learning algorithms.
• Classical ML and deep learning techniques across NLP, sequence modeling, RL, Recommendation systems, clustering, and time series.
• Experience with Python ML ecosystem (numpy, sklearn, pytorch, XGBoost, etc.)
• Strong written and verbal communication skills, ability to synthesize conclusions for non-experts, and overall bias towards simplicity and efficiency
• Intellectual curiosity and enthusiasm about continuous learning

Nice to have

• Designing end-to-end ML solutions from prototype to production.
• Experience in deploying ML workflows/models in production system
• Building or experimenting with LLMs, retrieval systems, generative models, and agentic AI workflows
• Familiarity with cloud based compute approaches GCP (or AWS, Azure), ML model development frameworks, and ML orchestration tools (Airflow, Kubeflow, VertexAI, etc)
• Experience with Kubernetes and Docker
• Clear track record of publishing or work related projects showing ability to develop cutting edge AI systems.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.