Senior Data Scientist

We’re Hiring: Senior Data Scientist – NLP Company: NUVO AI (Meril Group) Location: Vapi, Gujarat Mode: On-Site Experience: 5+ Years in Data Science/ML Engineering ( Minimum 3 years tenure in most recent organization in a relevant data science/ML role) Senior-level data scientist role focused on building and deploying production NLP systems on bare metal infrastructure. This position requires a research-oriented mindset with the ability to build first-in-class products by translating cutting-edge research into innovative production solutions. If you enjoy solving deep technical problems and pushing innovation—this role is for you. What You’ll Work On Build and deploy production-grade NLP systems using transformer models Implement RAG pipelines , embeddings, semantic search Manage and optimize bare-metal GPU servers , CUDA, and multi-GPU setups Design and optimize large-scale SQL pipelines Deploy and scale models via TorchServe/FastAPI/BentoML Drive MLOps : MLflow, W&B, monitoring, automated retraining Lead ML architecture, research-to-production pipelines, and cross-functional collaboration Required Skills 5+ years in ML/Data Science (with 3+ years in latest role) Proven ML production deployment experience Advanced SQL (tuning, indexing, Snowflake/BigQuery/Redshift) Strong Python, PyTorch/TensorFlow, HuggingFace Experience with LangChain/LlamaIndex, LoRA/QLoRA, vector DBs (Pinecone/FAISS) Linux admin, GPU cluster management, distributed training Docker, Kubernetes, CI/CD Cloud: AWS/GCP/Azure + hybrid infrastructure What You Bring Research-driven mindset Strong debugging, analytical & problem-solving skills Ability to work independently and own complex projects Clear communication with technical and non-technical teams Experience moving models from research → production Up-to-date knowledge of modern ML and NLP advancements Programming & ML Frameworks Python (advanced level, production-grade code) PyTorch or TensorFlow HuggingFace Transformers scikit-learn, XGBoost, LightGBM Infrastructure & DevOps Linux system administration Bare metal server management GPU cluster setup and configuration CUDA/cuDNN installation and driver management Multi-GPU distributed training setup Docker and Kubernetes CI/CD pipelines for ML workflows Production Deployment Model serving: TensorFlow Serving, TorchServe, FastAPI, BentoML MLOps: MLflow, Weights & Biases, Kubeflow Model monitoring and A/B testing Latency optimization and inference scaling Cloud & Data Engineering AWS, GCP, or Azure Apache Spark, Airflow/Prefect Understanding of on-premise and cloud hybrid architectures Leadership & Team Impact Lead end-to-end ML initiatives Define technical architecture Mentor junior ML engineers and data scientists Support hiring, code quality, and documentation standards How to Apply Send your resume to lisa.kapadia@nuvo.ai Or apply directly on LinkedIn.