Salary
≈ $22k – $48k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Senior · 8+ years exp
First seen by Alion on Sep 17, 2026.
Overview
Company
Impact
Profile match
Curl Analytics is a research company with expertise in Machine Learning, Blockchain and IoT. It builds predictive models to analyze the data for finding hidden patterns, provide business insights and enterprise grade solutions.
Looking for a Senior Data Scientist with a solid foundation in deep learning and traditional machine learning to deliver high-impact solutions that align with our AI product strategy. This position is perfect for someone who thrives in a fast-paced, innovative environment and is focused on executing sophisticated AI/ML projects from conception to deployment.
Responsibilities:
- Develop NLP models and algorithms for entity extraction and document processing.
- Fine-tune and optimize LLMs.
- Work on Retrieval-Augmented Generation to improve model responses and data retrieval processes.
- Ensure efficient serving, maintenance, and optimization of models.
- Provide mentorship and technical guidance to team members.
Requirements:
- Bachelor's or master's degree in computer science, data science, or related fields.
- 8+ years of experience with a strong portfolio in deep learning and traditional machine learning,
- Proficiency in Python and extensive experience with deep learning frameworks (e. g., PyTorch, TensorFlow).
- Track record of developing and deploying impactful AI models, with specific expertise in Document AI.
- Exceptional problem-solving skills and the ability to work with complex data sets to drive actionable insights
Must-Have Skills:
- Strong understanding of data science fundamentals and best practices.
- Proven experience in NLP and transformers.
- Hands-on experience with LLMs and their fine-tuning.
- Expertise in model serving and optimization.
- Proficiency in Python and extensive experience with deep learning frameworks (e. g., PyTorch, TensorFlow).
Good-to-Have Skills:
- Experience with cloud services (AWS, Google Cloud, Azure).
- Familiarity with ML platforms for LLMs.
- Knowledge of MLOps practices.
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