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As a Data Scientist, you will identify business trends and solve complex problems using large-scale data and advanced AI techniques. You will design, develop, and deploy high-impact solutions ranging from classical ML/DL to LLM-powered applications including RAG-based architectures and Agentic AI systems.

Key Responsibilities :

- Analyze existing digital products to understand current intelligent models and improve their performance, reliability, and scalability.
- Enhance traditional ML and DL pipelines by incorporating LLM-based capabilities such as summarization, Q&A;, reasoning, decision support, and copilots.
- Design and implement LLM-based solutions using Retrieval-Augmented Generation (RAG) to ground responses on enterprise data.
- Build Agentic AI workflows that enable multi-step task planning, tool and API invocation, and contextual memory management.
- Develop agent orchestration patterns such as multi-agent collaboration, deterministic workflow engines, and fallback mechanisms.
- Drive innovation through experimentation and contribute to invention disclosures and patents.
- Design and implement AI solutions for IoT, robotics, and automation use cases.
- Build and maintain scalable pipelines for model training, evaluation, and deployment.
- Manage experiment tracking, model versioning, and model registries.




- Define and track LLM-specific evaluation metrics including groundedness, faithfulness, hallucination rate, and safety.
- Monitor retrieval system quality using metrics such as precision, recall, and latency.

Required Qualifications :

- Masters degree in Computer Science, Electrical Engineering, Applied Mathematics, Statistics, or a related field (PhD preferred).
- Robust oral and written communication skills.
- Demonstrated ability to take ambiguous objectives and design innovative, flexible solutions.
- Proven track record of delivering impactful outcomes.

Technical Skills :

- Expertise in Large Language Models (LLMs) and building production-grade applications.
- Hands-on experience with RAG architectures, embeddings, vector search, and reranking mechanisms.
- Experience building tool-using agents and multi-step agent workflows.
- Familiarity with vector databases (e.g., Pinecone, Milvus, Weaviate, Elasticsearch).
- Experience with agent frameworks (e.g., LangChain, Semantic Kernel, LlamaIndex).
- Experience with LLMOps tooling: prompt management, evaluation harnesses, and observability.
- Cloud experience (Azure/AWS/GCP), containerization (Docker), and Kubernetes.

Behavioral Competencies :

- Strong ownership mindset and proactive leadership.
- Collaborative team player with an innovation-first approach.

📌 Data Scientist - Artificial Intelligence/Machine Learning (India)
🏢 Ajni Consulting
📍 India