Data Science Lead - LLM Models

Role Overview :

We are seeking an experienced Lead Applied AI/ML Engineer with ~8 years of hands-on and leadership experience in AI/ML and LLM-based solutions.

The ideal candidate will have deep expertise in fine tuning large models, building semantic/embedding search systems, deploying scalable AI services, and adding advanced capabilities such as real-time recommendations and voice interfaces.

This role involves leading a small team of engineers, guiding technical direction, and working closely with product, engineering, and business stakeholders to deliver AI-first features that directly impact millions of customers and merchants.

Job Description :

- Fine-tune and optimize large pre-trained models (LLMs, multimodal, CV, and NLP) for DigiHaat-specific tasks (menu understanding, fraud detection, recommendations, voice AI).

- Build embeddings and semantic search capabilities tailored for Indian menus, languages, and cuisines.

- Develop advanced suggestion and personalization engines leveraging ML and deep learning.

- Architect, deploy, and scale AI/ML models on cloud environments (AWS/GCP/Azure).

- Ensure reliability, latency optimization, and high availability of production AI services.

- Implement monitoring, retraining pipelines, and continuous improvement of deployed models.

- Lead initiatives to add voice-based ordering and interactions across customer and merchant platforms.

- Build hybrid AI systems (e.g., combining CV, NLP, and voice).

- Explore retrieval-augmented generation (RAG) and vector databases for domain-specific intelligence.

- Work closely with cross-functional teams to translate business problems into AI/ML solutions.

- Own the roadmap for AI capabilities across fraud detection, personalization, menu intelligence, and beyond.

Education :

- Masters or PhD in AI, Computer Science, Data Science, Statistics, or a related field.

- Prior leadership experience in AI/ML projects or managing small data science/AI teams.

- Experience with reinforcement learning, generative AI, or LLM-based applications.

Must-have attributes/Technical skills :

- 4+ years of experience in AI/ML engineering, model development, and applied AI solutions.

- Strong background in Python, TensorFlow, PyTorch, Scikit-learn, and ML frameworks.

- Proven experience in LLM finetuning, embeddings, and semantic search.

- Hands-on expertise with vector databases (Pinecone, Weaviate, FAISS, Milvus).

- Strong experience deploying models on cloud environments and managing MLOps workflows.

- Experience with recommendation engines, personalization algorithms, and fraud analytics.

- Knowledge of ASR (Automatic Speech Recognition) and TTS (Text-to-Speech) for voice AI.

- Solid understanding of microservices, API integrations, and distributed systems.

- Demonstrated leadership abilityexperience mentoring teams and delivering large-scale AI projects.