Senior Data Scientist

Looking for a senior AI engineer for the platform team. The ideal candidate will be responsible to derive key insights from huge sets of data, build models around those, and take them to production.

Responsibilities:

• Implementation: Analyze data to gain new insights, develop custom data models and algorithms to apply to distributed data sets at scale. Build continuous integration, test-driven development, and production deployment frameworks
• Architecture: Design the architecture with the Data and DevOps engineers
• Ownership: Take ownership of the accuracy of the models and coordinate with the stakeholders to keep moving forward
• Releases: Take ownership of the releases and pre-plan according to the needs
• Quality: Maintain high standards of code quality through regular design and code reviews.

Requirements:

• Extensive hands-on experience in Python/R is a must.
• Proficiency in ML/DL frameworks and tools (e. g. Pandas, Numpy, Scikit-learn, Pytorch, Lightning, Huggingface)
• Strong command in low-level operations involved in building architectures for Ensemble Models, NLP, CV (eg. XGB, Transformers, CNNs, Diffusion Models)
• Experience with end-to-end system design; data analysis, distributed training, model optimisation, evaluation systems, for large-scale training & prediction.
• Experience working with huge datasets (ideally in TeraBytes) would be a plus.
• Experience with frameworks like Apache Spark (using MLlib or PySpark), Dask etc.
• Practical experience in API development (e. g., Flask, FastAPI).
• Experience with MLOps principles (scalable development & deployment of complex data science workflows) and associated tools, e. g. MLflow, Kubeflow, ONNX
• Bachelor's degree or equivalent experience in Engineering or a related field of study
• 2+ years of AI engineering experience
• Strong people, communication, and problem-solving skills