Data Science Specialist

Please find the below details :

Role :
Data Science Lead

Experience : 4-7 years

Location :
Delhi

Mode : WFO (5 days)

JOB DESCRIPTION :

- Fine-tune and optimize large pre-trained models (LLMs, multimodal, CV, and NLP).
- 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 :

- Master’s 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, Tensor Flow, PyTorch, Scikit-learn, and ML frameworks.
- Proven experience in LLM fine tuning, 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 ability—experience mentoring teams and delivering large-scale AI projects