Data Scientist

Responsibilities:

• Design, build, and deploy production-ready Generative AI and Voice AI applications.
• Develop intelligent AI agents using LLMs, NLP, and modern AI frameworks.
• Fine-tune open-source and proprietary LLMs for domain-specific use cases.
• Build Agentic AI workflows, RAG pipelines, and enterprise AI solutions.
• Work on speech understanding, conversational AI, and voice-based applications.
• Collaborate with backend, product, and platform teams to take AI solutions from research to production.
• Evaluate emerging AI models and optimise performance, latency, and scalability.

Requirements:

• 1-4 years of experience in AI/ML, Data Science, or Generative AI.
• Strong programming skills in Python.
• Hands-on experience with Generative AI, LLMs, NLP, Transformers, Prompt Engineering, RAG, and Agentic AI.
• Experience with Hugging Face Transformers, LangChain/LangGraph, LlamaIndex, CrewAI, or similar frameworks.
• Experience with LLM fine-tuning (LoRA/QLoRA), model evaluation, and deployment.
• Good understanding of vector databases, semantic search, and modern AI architectures.
• Experience with AWS and deploying AI applications in production.
• Strong problem-solving and analytical skills.

Preferred Experience:

• Candidates with experience in Voice AI, Conversational AI, Speech AI, ASR (Automatic Speech Recognition), TTS (Text-to-Speech), Speech-to-Text, or Telephony AI platforms will be strongly preferred.
• Experience working on real-time voice agents, call automation, IVR systems, or multilingual speech applications is a significant advantage.
• Experience with Docker, Kubernetes, and production-scale AI deployments is a plus.