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# Data Scientist with Databricks

- **Company:** Intersources Inc.
- **Location:** Santa Clara, CA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Artificial Neural Networks, Microsoft Azure, Big Data, Computer Programming, Python (Programming Language), Machine Learning, Open Source Technology, Tensorflow, Reinforcement Learning, High Performance Computing, Pytorch, Large Language Models, Deep Learning, Generative AI, Information Technology, Optimization Algorithms, Unsupervised Learning, Databricks
- **Published:** August 6, 2026
- **Apply:** https://www2.jobdiva.com/portal/?a=62jdnw10t7d77ytz0lbaey9qxonk3b05a9tqw96rb7z6hlfo7xj79l9g6mp6aj2o&compid=0/jobs/28447803#/jobs/28447803

## About the Role

Good GenAI capabilities, with hands-on experience in Tradition ML/deep learning.
Deep learning expertise is mandatory for a Data science role.
Candidates should have a good appetite for research and exploration while working.
should have a fair bit of experience in DL/neural networks or ML. Especially how CNN, RNN work. Details on How Transformers work. What are the various components in neural network design? And all optimization algorithms used in Neural nets., B.E./ B. Tech / M. Tech/ MCA in computer science, artificial intelligence, or a related field.
6+ years of IT experience with a min of 3+ years in Data Science (AI/ML).
Strong programming skills in Python.
Experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
Hands-on AI/ML modeling experience of complex datasets combined with a strong understanding of the theoretical foundations of AI/ML(Research Oriented).
Expertise in most of the following areas: supervised & unsupervised learning, deep learning, reinforcement learning, federated learning, time series forecasting, Bayesian statistics, and optimization.
Hands-on experience on design, and optimizing LLM, natural language processing (NLP) systems, frameworks, and tools.
Building RAG applications independently using available open source LLM models.
Comfortable working in the cloud and high-performance computing environments (e.g., AWS/Azure/GCP, Databricks).



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