Lead Data Scientist

Role & responsibilities

• Role Recommendation Engine, for Data accuracy-

Develop, train, and fine-tune machine learning and deep learning models for diverse business use cases. With an Overall experience of (6-12 Years)

• Work with Generative AI and LLMs, including customizing, fine-tuning, and deploying models for real-world applications.

• Stay updated with the latest advancements in Machine Learning, Deep Learning, and Generative AI, and incorporate them into projects.

Required Skills:

• Machine Learning Frameworks: Proficiency in Scikit-learn, TensorFlow or PyTorch.

• Deep Learning: Experience building and training deep learning models, including CNNs, RNNs, Transformers, and other architectures.

• Generative AI: Hands-on experience with Generative AI models, including fine-tuning and deploying LLMs.

• Programming: Strong skills in Python; familiarity with libraries like NumPy, pandas, and Matplotlib.

• Data Handling: Experience working with structured and unstructured data, including text, images, and time-series.

Good to have Skills:

• Exposure to tools like Hugging Face Transformers for working with LLMs.

• Understanding of MLOps practices, including CI/CD pipelines for ML models.

• Experience with GPU-accelerated computing.

• Experience with distributed training frameworks (e.g., Horovod, PyTorch Lightning).

• Cloud Platforms: Familiarity with cloud services like AWS

Qualifications:

• Bachelors or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.

• 6+ years of professional experience in Machine Learning and Deep Learning.

• Proven track record of deploying ML/DL models in production environments.