Staff Machine Learning Scientist

Nykaa · Bengaluru

  • Experience7–11 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelexecutive
  • Posted2 Sept 2026
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About Nykaa

Nykaa is hiring in Bengaluru in ecommerce retail. This role looks for around 7+ years of experience.

Skills

  • Machine Learning
  • AdTech
  • Performance Marketing
  • Digital Advertising
  • Recommender Systems
  • CTR/CVR Prediction
  • Learning-to-Rank
  • Bidding Strategies
  • Auction Dynamics
  • Bid Optimisation
  • Budget Optimisation
  • Target ROAS Optimisation
  • Campaign Automation
  • Multi-objective Optimisation
  • Personalisation
  • Generative AI
  • Multi-Armed Bandits
  • Representation Learning
  • Embeddings
  • Auction Systems
  • Ads Marketplaces
  • Real-time Inference
  • Model Serving
  • Model Monitoring
  • ML Observability
  • Python
  • PyTorch
  • TensorFlow
  • XGBoost
  • LightGBM
  • scikit-learn
  • PySpark
  • SQL
  • Distributed Data Processing
  • Online Experimentation
  • A/B Testing
  • Incrementality Measurement
  • Statistical Experiment Design

The role

A machine learning scientist at an e-commerce retail company designs production machine learning systems for advertising and recommendation systems, applying Learning-to-Rank and Generative AI. Builds real-time inference services and conducts online experimentation.

Full job description

Requirements:

Bachelor's, Master's, or PhD in Computer Science, Machine Learning, Statistics, Mathematics, or a related technical discipline from a reputed institution.

7+ years of experience building and deploying production-grade Machine Learning systems.

At least 5+ years of hands-on experience in AdTech, Performance Marketing, Digital Advertising, or large-scale Recommender Systems.

Proven track record of designing, developing, and deploying high-impact ML solutions as a senior individual contributor.

Experience taking ML models from research and experimentation through production deployment and continuous optimisation.

Deep expertise in one or more of the following domains: CTR/CVR prediction, Learning-to-Rank and recommendation systems, Bidding strategies and auction dynamics, Bid and budget optimisation, Target ROAS optimisation, Campaign automation, Multi-objective optimisation.

Personalisation and recommendation systems.

Generative AI for creative optimisation and advertiser assistance.

Technical Skills:

Strong understanding of: Learning-to-Rank (LTR), Multi-Armed Bandits and exploration/exploitation strategies, Representation Learning and Embeddings, Auction Systems and Ads Marketplaces, Multi-objective Optimisation.

Real-time inference and low-latency model serving.

Model monitoring and production ML observability.

Strong programming skills in Python.

Hands-on experience with modern ML frameworks including: PyTorch, TensorFlow, XGBoost, LightGBM, Scikit-learn.

Experience processing large-scale datasets using: PySpark, SQL, Distributed data processing frameworks.

Strong expertise in: Online experimentation, A/B Testing, Incrementality Measurement, Statistical Experiment Design.

Experience working with cloud-native ML infrastructure and production-scale model deployment is highly preferred.