LLM Data Scientist
About Us
Giniminds partners with organizations to transform them into real-time enterprises.
We specialize in AI-driven modernization—spanning data protection, real-time analytics, streaming platforms, information security, B2B integration, and enterprise application integration. With a strong partner ecosystem and a data-driven strategy, we deliver agile, scalable, and cutting-edge solutions that drive meaningful business outcomes.
Job Description
Job Title: LLM Data Scientist (2+ Years Experience)
Location: Bengaluru
Employment Type: Full-time
Industry: AI Platforms / Enterprise AI Solutions
About the Role
We are looking for an experienced LLM Data Scientist who can design, develop, and optimize Agentic AI systems and enterprise-grade AI platforms. The ideal candidate has hands-on experience with LangChain, LLM orchestration frameworks, vector databases, and AI agents that automate complex business workflows. You will work closely with product, engineering, and AIOps teams to build scalable, production-ready AI capabilities.
Key Responsibilities
LLM & Agentic AI Development
- Build, evaluate, and optimize LLMs, knowledge-grounded models, and agentic pipelines.
- Develop multi-agent systems, tool-based agents, retrieval-augmented agents, and workflow automations.
- Implement LangChain, LangGraph, LLM flows, or equivalent frameworks for orchestration.
- Fine-tune open-source LLMs (Llama, Mistral, Gemma, etc.) for domain-specific tasks.
Platform & Pipeline Building
- Design and deploy end-to-end AI pipelines—from ingestion to inference & monitoring.
- Integrate LLM-based systems with external APIs, SaaS tools, and enterprise systems.
- Build reusable modules, prompt libraries, agent frameworks, and evaluation suites.
- Work closely with MLOps teams for optimization, caching, latency reduction, and cost control.
Data Science & Model Engineering
- Perform advanced prompt engineering, RAG tuning, embeddings design, and model evaluation.
- Design experiments, analyze model performance, and implement continuous improvement cycles.
- Develop structured datasets for LLM training, synthetic data generation, and data quality validation.
Collaboration & Architecture
- Partner with architects to design scalable AI platform architecture.
- Translate business requirements into technical designs and AI workflows.
- Document solutions, maintain repos, and follow best practices for reproducibility and governance.
Required Skills & Experience
- 2+ years hands-on experience in Data Science and NLP,LLM
- Strong experience in Python, LangChain, LangGraph, OpenAI / Anthropic / Google APIs, and agentic AI frameworks.
- Experience with vector databases (Pinecone, Weaviate, Milvus, Chroma).
- Knowledge of RAG architectures, retrieval optimization, embedding models, and observability tools.
- Familiarity with LLM tuning (LoRA, QLoRA, SFT, RLHF).
- Experience deploying models on cloud platforms (AWS, Azure, GCP) or on-prem GPU clusters.
- Understanding of API integration, scalable microservices, and asynchronous job systems.
Preferred / Good to Have
- Experience building enterprise AI platforms, AI copilots, or workflow automation systems.
- Hands-on exposure to agent frameworks like CrewAI, AutoGen, Haystack Agents, or custom tool-based agents.
- Familiarity with LLM evaluation frameworks, hallucination detection, guardrails, and safety tooling.
- Experience with Docker, Kubernetes, and end-to-end CI/CD.
Soft Skills
- Strong problem-solving and system thinking
- Ability to work in a fast-paced environment
- Excellent communication & documentation
- Product mindset with focus on reliability and scalability
Why Join Giniminds
- Work on cutting-edge Agentic AI & LLM platform initiatives
- Opportunity to build foundational AI components used across the organization
- Culture of innovation, experimentation, and ownership
Education
- Bachelor’s degree in Computer Science, or related field.
Pay: ₹1,000,000.00 - ₹1,500,000.00 per year
Benefits:
- Health insurance
- Life insurance
- Paid sick time
- Paid time off
- Provident Fund
Work Location: In person
