Staff Data Scientist

OneShot AI; Bengaluru; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

OneShot AI in Bengaluru is seeking a senior AI engineer to design, build, and deploy NLP and Generative AI solutions. You will develop and optimize transformer-based models, work with LLMs, and drive production-grade pipelines from experimentation to deployment.

The role requires hands-on experience with PyTorch/TensorFlow, LangChain, and Hugging Face Transformers, plus strong Python coding skills and a track record in production AI systems.

Qualifications

• 6+ years of experience in Data Science, ML, or AI Engineering.
• Strong NLP and deep learning background.
• Hands-on experience building and deploying ML/AI models in production.
• Strong experience with transformer architectures and modern NLP frameworks.
• Proven experience with LLMs and Generative AI systems.

Responsibilities

• Design, build, and deploy NLP and Generative AI solutions.
• Develop and optimize ML/DL models, including transformers.
• Work with LLMs, prompt engineering, and RAG pipelines.
• Build scalable model pipelines from experimentation to production.
• Collaborate with engineering and product teams to translate business problems into AI solutions.
• Conduct model evaluation, experimentation, benchmarking, and optimization.
• Write production-quality Python code and contribute to AI platform architecture.
• Stay updated with advancements in LLMs and GenAI ecosystems.

Skills

NLP

Deep Learning

Python

LLMs

RAG pipelines

Prompt engineering

Production deployment

Distributed training

MLOps

AI orchestration

Tools

PyTorch

TensorFlow

Hugging Face Transformers

LangChain

Job description

Responsibilities:

• Design, build, and deploy NLP and Generative AI solutions for real-world applications.
• Develop and optimize machine learning and deep learning models, including transformer-based architectures.
• Work extensively with Large Language Models (LLMs), prompt engineering, fine-tuning, RAG pipelines, and agentic workflows.
• Build scalable model pipelines from experimentation to production deployment.
• Collaborate with engineering and product teams to translate business problems into AI solutions.
• Conduct model evaluation, experimentation, benchmarking, and performance optimization.
• Write production-quality Python code and contribute to AI platform architecture.
• Stay up to date with the latest advancements in LLMs, GenAI frameworks, and open-source AI ecosystems.

Requirements:

• 6+ years of experience in Data Science, Machine Learning, or AI Engineering.
• Strong background in Natural Language Processing (NLP) and deep learning.
• Hands-on experience building and deploying ML/AI models in production.
• Strong experience with transformer architectures and modern NLP frameworks.
• Proven experience working with Large Language Models (LLMs) and Generative AI systems.
• Strong coding skills in Python and experience with ML/AI libraries such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, or similar frameworks.
• Experience with model fine-tuning, embeddings, vector databases, RAG pipelines, and prompt engineering.
• Solid understanding of data structures, algorithms, experimentation, and model evaluation techniques.
• Ability to independently drive projects in ambiguous and fast-paced environments.

Preferred Qualifications:

• Experience with multi-agent systems, AI orchestration, or autonomous workflows.
• Exposure to distributed training, inference optimization, or scalable AI infrastructure.
• Experience deploying AI systems on cloud platforms such as AWS, GCP, or Azure.
• Familiarity with MLOps, CI/CD pipelines, and monitoring production AI systems.
• Research or applied experience in conversational AI, semantic search, summarization, or recommendation systems.

Ideal Candidate:

• The ideal candidate combines strong data science fundamentals with hands-on GenAI engineering expertise.
• You should be comfortable moving from research and experimentation to scalable production systems while maintaining high ownership, speed, and technical rigor.