Data Scientist

Job Title: Data Scientist
Experience Required: 7+ Years
Work Location: Bangalore
Mode of Hire: Contract (Onsite)
Joining Timeline: Immediate Joiner

Job Summary:
As a Data Scientist, you will leverage your analytical, statistical, and machine learning expertise to extract meaningful insights from diverse datasets and guide data-informed decision-making. You will build and deploy predictive models, collaborate with cross-functional teams, and translate complex findings into business value. Your work will empower the organization to solve strategic challenges and create impactful data-driven solutions.

Key Responsibilities

• Develop and implement AI/ML/LLM‑based applications using Python, scripting and production pipelines.

• Design and deploy Retrieval‑Augmented Generation (RAG) workflows leveraging LLaMA (and other open models) via frameworks such as LangChain, LlamaIndex, PEFT, LoRA, QLoRA.

• Integrate, deploy, and optimize vector databases—e.g., pgvector (Postgres), ChromaDB, Pinecone, Milvus, etc.—for semantic search and embedding workflows

• Leverage Databricks environment (Delta Lake, MLflow, Apache Spark) for scalable data processing and ML model development and deployment

• Convert natural language queries into structured queries (e.g. SQL) for relational databases (Postgres) using LLM‑based text2SQL or prompt‑to‑SQL mechanisms

• Build backend APIs (Flask, FastAPI) to expose AI capabilities and integrate with product teams.

• Drive full ML/Ops pipeline lifecycle: version control, CI/CD, monitoring, evaluation, retraining.

• Collaborate closely with product managers, engineers, and designers to rapidly ship new AI applications under tight deadlines.

• Support customer or stakeholder-facing demoing or POCs—communicate technical concepts clearly to non-technical audiences.

Requirements
Technical Expertise (6–8+ years experience, or equivalent impact in startups)

• Python (pandas, numpy, fluency with scripting, package management, virtual environments).

• Databricks (Apache Spark, MLflow, Delta Lake) usage in production-grade ML or GenAI workflows.

• Hands-on working experience with LLaMA / open‑source LLMs, fine-tuning, instruction tuning, prompt engineering, model serving.

• Deep familiarity with vector DBs (e.g., pgvector on Postgres, Milvus, Chroma, Pinecone), embedding generation, similarity search, indexing strategies

• Experience building RAG architectures, agents, retrieval pipelines using LangChain, LlamaIndex, Hugging Face transformers.

• Proficient with ML/DL frameworks: PyTorch, TensorFlow, Transformers, scikit-learn.

• Designing and deploying scalable applications using PostgreSQL, and seamlessly combining relational and vector database capabilities.

• Familiarity with cloud environments (AWS/GCP/Azure), containerization (Docker), orchestration (Kubernetes) and CI/CD pipelines.

• Strong understanding of MLOps/LLMOps frameworks and cost-optimized deployment patterns.

Good to Have :

• Experience with Quantization techniques (LoRA, QLoRA, GPTQ), PEFT, model compression strategies.

• Familiarity with Knowledge Graphs or integration with graph DBs (Neo4j, LlamaIndex).

• Prior experience in building multi‑agent systems, orchestration frameworks like Autogen, LangGraph.

• Exposure to shoulder use cases: AWS Lambda, Redis Stack, Elasticsearch with vector search.

Job Type: Contractual / Temporary
Contract length: 6 months

Pay: ₹140,000.00 - ₹160,000.00 per month

Application Question(s):

• Do you have experience in Python ?
• Do you have experience in Databricks ?
• Do you have experience in working with LLAMA models ?

Work Location: In person