Data Science Professionals (LLM & Core NLP)

Responsibilites

• Core NLP & LLM Development
• Design and implement state-of-the-art NLP architectures, focusing on Large Language Models (LLMs), Vision-Language Models (VLMs), and Agentic AI systems (MCP, A2A protocols, tool-calling).
• Construct and optimize deep learning models using advanced techniques such as Low-Rank Adaptation (LoRA/PEFT), quantization, distillation, and advanced prompting strategies (e.g., Chain-of-Thought, LLM-as-a-Judge).
• Develop and deploy Generative AI solutions for high-impact areas including search, recommendation engines, catalog management, user-generated content areas, and moderation.
• Build robust RAG (Retrieval-Augmented Generation) systems, handling the full pipeline from embedding generation and vector databases to context retrieval and answer synthesis.
• Data Strategy & Application
• Drive solutions from free-text data across multiple languages, utilizing extensive data mining and statistical analysis to extract actionable insights.
• Conduct exploratory data analysis (EDA)and rigorous error analysis to identify hidden patterns, navigate complex datasets, and establish ground truths.
• Innovate in data preprocessing, including the design of automated label generation workflows and data cleaning pipelines to ensure high-quality model input.
• Business Impact & Collaboration
• Partner with engineering and product stakeholders to identify opportunities where AI can solve critical business problems in mobile commerce and ad-tech.
• Synthesize complex technical methodology into clear business strategies, communicating findings effectively to management to drive decision-making.
• Champion a data-driven culture within the organization, advocating for best practices in machine learning and data science.
• Track and apply the latest developments in NLP and Gen AI literature to maintain a competitive edge in e-commerce business problems.

Expected Qualifications

• Essential Background & Skills
• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, Mathematics, or a related field.
• Experience: 3+ years of hands-on experience in Data Science, with a specific focus on NLP, Generative AI, or LLM development
• Technical Proficiency: Strong command of Python and SQL. Extensive experience with deep learning frameworks (PyTorch, TensorFlow) and NLP libraries (Hugging Face Transformers, LangChain, Pandas, Scikit-learn).
• LLM Expertise: Proven track record in training, fine-tuning, and evaluating LLMs. Experience with OpenAI/Gemini APIs (chat/completions, embeddings, fine-tuning, tool-calling).
• Core NLP Knowledge: Deep understanding of foundational concepts including summarization, QA, information extraction, clustering, and semantic search.
• Communication: Excellent written and verbal communication skills in English, with the ability to explain complex AI concepts to non-technical teams.


• Preferred Qualifications (Nice-to-haves)
• Advanced Education: A PhD in AI, NLP, or Data Science.
• Domain Experience: Prior experience in mobile commerce, ad-tech, or self-service business models.
• Soft Skills: A "can-do" attitude with a curiosity for "impossible" questions, strong interpersonal skills, and a result-oriented mindset.