Lead Data Scientist
- India
- Permanent
- Full-time
As a Lead Data Scientist, you will serve as a senior technical expert, driving the design and delivery of advanced AI/ML and LLM-based solutions from concept to production. This is an individual contributor role with a strong alignment and coordination component — ensuring technical excellence, stakeholder engagement, and seamless integration across product, engineering, and delivery teams.The ideal candidate combines deep hands-on expertise in AI/ML/LLM/RAG systems with practical problem-solving acumen, delivering scalable solutions to complex business challenges.Responsibilities:1. AI/ML/LLM/RAG Solution Development
- Architect and implement end-to-end AI/ML solutions, leveraging structured and unstructured data (text, images, metadata, multimodal sources).
- Lead development and deployment of LLM-powered systems for classification, retrieval-augmented generation (RAG), information extraction, and summarization.
- Apply advanced techniques such as LoRA, PEFT, quantization, and model distillation to optimize model performance, latency, and cost.
- Design and implement robust retrieval pipelines with vector search, hybrid retrieval, and reranking strategies.
- Ensure code quality, reproducibility, and model governance across the AI/ML lifecycle — from experimentation to production release.
- Establish and promote best practices for data processing, feature engineering, model evaluation, and monitoring.
- Conduct rigorous performance benchmarking and failure analysis, ensuring models meet accuracy, throughput, and reliability targets.
- Partner closely with product managers, engineers, and customer-facing teams to translate business needs into AI/ML requirements.
- Align model development milestones with product release schedules, ensuring timely and high-quality delivery.
- Serve as a technical advisor during project scoping, prioritization, and release readiness reviews.
- Stay current with cutting-edge research in AI, ML, NLP, LLMs, multimodal models, retrieval systems, and document intelligence..
- Proactively identify opportunities to enhance existing algorithms and develop novel approaches.
- Share learnings through internal tech talks, documentation, and mentorship to foster a culture of innovation.
- LLM & GenAI Expertise: Minimum 2 years of hands-on experience fine-tuning, prompting, and deploying LLMs (commercial and open-source) such as GPT, Claude, Gemini, Mistral, LLaMA, Falcon, Vicuna, MPT, T5.
- NLP & Information Retrieval: At least 4 years working with NLP tasks — classification, NER, summarization, QA, RAG architectures — using Transformer-based models (BERT, RoBERTa, T5, etc.).
- Deep Learning Frameworks: Strong experience with PyTorch and/or TensorFlow for model training and deployment.
- Coding & Engineering: Expert-level Python; strong SQL; experience with FastAPI/Flask for serving models; Git proficiency.
- Data & Infra: Proficiency with PostgreSQL and vector databases (Pinecone, Qdrant, Weaviate, etc.); familiarity with Docker/Kubernetes.
- MLOps & Scaling: Experience with MLFlow/KubeFlow/SageMaker or equivalent for training pipelines, deployment, and monitoring at scale.
- Prompt Engineering: Skilled in CoT, self-consistency, ToT, and advanced prompting for LLM optimization.
- Ability to simplify complex technical concepts for diverse stakeholders.
- Strong problem-solving skills with a bias toward scalable, maintainable solutions.
- Excellent communication and documentation skills.
- Track record of aligning technical execution with business priorities and delivery timelines.
- Experience with multimodal models (text + vision).
- Knowledge of knowledge graph construction and integration.
- Familiarity with cloud services (AWS preferred).
- Exposure to compliance and governance requirements in AI systems
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