Data Scientist GEN AI/Classical ML

# Generative AI – Data Science & Architecture ## Company Overview Not specified. ## Job Summary We are seeking skilled professionals across levels (L3, L4, L5) with expertise in Generative AI, Large Language Models (LLMs), Python, and MLOps. Candidates will contribute to the design, development, and scaling of Generative AI platforms and solutions that drive business transformation and enhance customer impact. ## Responsibilities ### L3 (Senior Engineer / Data Scientist) - Develop and fine-tune LLMs using frameworks such as Hugging Face and LangChain. - Implement Retrieval-Augmented Generation (RAG) pipelines, embeddings, and prompt engineering solutions. - Build Python-based machine learning (ML) models, APIs, and workflows for Generative AI use cases. - Collaborate with MLOps teams to integrate Continuous Integration/Continuous Deployment (CI/CD), monitoring, and model deployment pipelines. ### L4 (Lead / Senior ML Engineer) - Lead the design and implementation of Generative AI applications across domains like customer support, content generation, and code generation. - Optimize inference performance and cost efficiency for LLM-based solutions. - Define and enforce best practices for model training, fine-tuning (LoRA, PEFT), and experimentation. - Mentor L3 engineers/data scientists and ensure quality delivery. - Collaborate with stakeholders to identify high-value use cases and deliver impactful pilots/Proofs of Concept (PoCs). ### L5 (Architect) - Define enterprise-wide Generative AI architecture blueprints, system designs, and governance models. - Select and integrate foundational models (e.g., GPT, Claude, LLaMA, Mistral) based on business and technical needs. - Drive innovation and adoption of advanced architectures, including multimodal, diffusion models, and hybrid AI. - Guide teams on architecture-level decisions including scalability, security, and compliance. - Collaborate with product, data, and cloud teams to enable large-scale, cloud-native deployment on platforms like AWS, GCP, or Azure. - Stay at the forefront of the Generative AI landscape and evaluate emerging tools and frameworks. ## Qualifications - **Education:** Bachelor’s or Master’s in Computer Science, Artificial Intelligence, Data Science, or a related field (PhD is a plus). ### Experience: - **L3:** 5–8 years in Data Science/Machine Learning, with hands-on experience with Generative AI/LLMs. - **L4:** 8–12 years in AI/Machine Learning, with proven experience leading Generative AI solutions. - **L5 (Architect):** 12–15 years in AI/Machine Learning and software engineering, with at least 3 years in Generative AI & LLM architectures. ### Core Skills (All Levels) - Proficiency in Python and frameworks: Hugging Face Transformers, LangChain, PyTorch, TensorFlow, OpenAI API. - Expertise in LLMs, transformers, prompt engineering, and fine-tuning (LoRA, PEFT). - Experience with vector databases (Pinecone, FAISS, Weaviate) and RAG pipelines. - Strong understanding of MLOps practices, including CI/CD, monitoring, model versioning, drift detection, and performance optimization. - Familiarity with cloud-native architectures (AWS/GCP/Azure), containerization (Docker/Kubernetes), and API integration. ### Leadership & Architectural Skills (Primarily L4 & L5) - Ability to mentor, guide, and review team deliverables. - Strong cross-functional collaboration and stakeholder management skills. - Proven record of delivering scalable, secure, and cost-effective Generative AI systems. ## Preferred Skills Not specified. ## Experience Experience requirements vary by level: - L3: 5–8 years - L4: 8–12 years - L5 (Architect): 12–15 years ## Environment Work setting details are not specified. ## Salary Salary details are not specified. ## Growth Opportunities Not specified. ## Benefits Not specified.