About the role
Responsibilities:
- Design, develop, and deploy machine learning models, algorithms, and systems to solve complex business problems for Myntra Recsys, Search, Vision, SCM, Pricing, Forecasting, Trend, and Virality prediction, Gen AI, and other areas.
- Theoretical understanding and practice of machine learning and expertise in one or more of the topics, such as NLP, Computer Vision, recommender systems, and optimization.
- Implement robust and reliable software solutions for model deployment.
- Support the team in maintaining machine learning pipelines, contributing to tasks like data cleaning, feature extraction, and basic model training.
- Participate in monitoring the performance of machine learning models, gaining experience in using statistical methods for evaluation.
- Working with the Data Platforms teams for understanding and collecting the data.
- Conduct performance testing, troubleshooting, and tuning as required.
- Stay current with the latest research and technology and communicate your knowledge throughout the enterprise.
Requirements:
- Master's/PhD in Computer Science, Mathematics, Statistics/related fields, or 3+ years of relevant industry experience with a Bachelor's degree.
- Proficiency in Python or one other high-level programming language.
- Theoretical understanding of statistical models such as regression, clustering, and ML algorithms such as decision trees, neural networks, etc.
- Strong written and verbal communication skills.
- Intellectual curiosity and enthusiasm for continuous learning.
- Experience developing machine learning models in Python, or equivalent programming language.
- Basic familiarity with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn.
- Introductory understanding of statistics as it applies to machine learning.
- Ability to manage and prioritize your workload and support his/her manager.
- Experience with SQL and/or NoSQL databases.
Nice to Have:
- Publications or presentations in recognized Machine Learning and Data Science journals/conferences.
- Experience with ML orchestration tools (Airflow, Kubeflow, or MLFlow).
- Exposure to GenAI models.