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Sr Data Scientist

Sr Data Scientist

Tanla Platforms

5 - 10 years

30 - 35 Lacs

hyderabad

Posted:1 day ago| Platform:

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Skills Required

product engineering usage compliance neural networks gcp analytical cloud analytics monitoring python

Work Mode

Work from Office

Job Type

Full Time

Job Description

The role involves designing, building, and fine-tuning large language models (LLMs) for both text and voice-based applications. The candidate will drive innovation in generative AI solutions, implement end-to-end ML pipelines, and ensure reliability, scalability, and ethical AI deployment across Tanla s AI initiatives.

What youll be responsible for?

Design, develop, and deploy large language models (LLMs) for both text and voice use cases.
Implement fine-tuning, prompt engineering, and optimization for domain-specific Gen AI solutions.
Architect and manage ML systems leveraging neural networks and transformer architectures.
Drive implementation of Retrieval-Augmented Generation (RAG) systems and AI agents.
Collaborate with cross-functional teams to build scalable AI products.
Conduct data preprocessing, model evaluation, and continuous model improvement.
Lead projects on responsible AI deployment, bias detection, and model governance.
Mentor junior engineers and contribute to the AI/ML Centre of Excellence at Tanla.

Qualification and other skills

Qualification:

Bachelor s or master s degree from any Tier 1 institution

Experience:

5-10 Years

Behavioral Skills:

Strong analytical and problem-solving abilities
Excellent communication and collaboration skills
Proactive, innovative, and results-driven mindset
Ability to work in a fast-paced, dynamic environment
Commitment to responsible AI practices and continuous learning

What youd have?

Deep understanding of Neural Networks and Transformer-based architectures (GPT, BERT, Llama, etc.)
Hands-on experience with LLM fine-tuning, prompt engineering, and generative AI frameworks (LangChain, LlamaIndex, AutoGen, CrewAI)
Experience building AI systems for both Voice and Text modalities
Proficiency in Python, TensorFlow, PyTorch, Hugging Face, and related ML frameworks
Strong understanding of RAG systems and vector databases (Pinecone, Weaviate, ChromaDB)
Expertise in ML Ops, model deployment, and monitoring (Kubernetes, Docker, CI/CD)
Knowledge of cloud-based AI services (AWS Sagemaker, Azure ML, GCP Vertex AI)
Familiarity with NLP, Speech Recognition, and Conversational AI
Sound understanding of AI ethics, governance, and compliance

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