Senior Data Scientist

Overview

Position Overview

Key Responsibilities

• Design, build, and optimize LLM-based solutions for tasks such as text understanding, summarization, semantic search, dialogue systems, and reasoning.
• Develop and orchestrate agentic workflows, integrating LLMs with tools, APIs, and data pipelines for autonomous task execution.
• Fine-tune and align LLMs on domain-specific datasets, leveraging techniques such as RLHF, prompt engineering, retrieval-augmented generation (RAG), and knowledge grounding.
• Architect multi-modal AI pipelines combining LLMs with computer vision, knowledge graphs, and structured data.
• Ensure scalability, efficiency, and reliability of deployed models on cloud and edge environments.
• Stay updated with the latest research in GenAI, agents, and applied AI, translating findings into innovative product features.
• Collaborate with software engineers, data engineers, and product managers to integrate AI models into production systems.
• Document methodologies, publish internal best practices, and present findings to stakeholders.

Qualifications

• Master’s or Ph.D. in Computer Science, Data Science, Machine Learning, Applied Mathematics, or related field.
• Advanced research and practical experience with large-scale machine learning models.
• 5+ years of hands-on experience in AI, machine learning, or intelligent agent system development.

Experience

• Proven experience in developing and deploying LLM-powered solutions.
• Strong background in natural language processing (NLP), applied machine learning, and GenAI projects.
• Experience with orchestration frameworks (LangChain, LlamaIndex, Haystack, or equivalent).

Skills

• Proficiency in Python and ML frameworks (TensorFlow or PyTorch, Hugging Face).
• Hands-on with LLM fine-tuning, evaluation, and optimization.
• Knowledge of RAG pipelines, embeddings, and vector databases (e.g., FAISS, Pinecone, Milvus).
• Familiarity with agentic architectures and workflow automation frameworks.
• Familiarity with backend frameworks (e.g., FastAPI), containerization (Docker), and databases (PostgreSQL, Redis).
• Strong analytical, problem-solving, and research skills.
• Excellent communication skills to explain technical concepts to diverse audiences.
• Ability to thrive in fast-paced, collaborative environments.

Preferred

• Experience with multi-agent systems, autonomous reasoning, and planning frameworks.
• Experience with vector databases (FAISS, Pinecone, Milvus) and orchestration frameworks (LangChain, LlamaIndex, Haystack).
• Knowledge of Model Context Protocol (MCP) and reasoning models is a plus.
• Familiarity with responsible AI, bias mitigation, and data privacy in LLM systems.
• Knowledge of real-time applications (e.g., chatbots, copilots, AI agents). Knowledge of AI coding tools (Cursor, Claude code, OpenAI Codex, github copilot