Senior Data Scientist

12 hours ago

India Meril Full time

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 Or apply directly on LinkedIn.

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