Hiring for Sr. Data Scientist (AI / ML, Deep : 5 Years - 12 Years
Location : Mumbai, Hyderabad, Bangalore, Gurugram
Mode : Experience :
- Strong Senior Data Scientist ( AI / ML / GenAI) Profile
- Must have a minimum of 5+ years of experience in designing, developing, and deploying Machine Learning / Deep Learning (ML / DL) systems in production
- Must have strong hands-on experience in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX.
- Must have 1+ years of experience in fine-tuning Large Language Models (LLMs) using techniques like LoRA / QLoRA, and building RAG (Retrieval-Augmented Generation) pipelines.
- Must have experience with MLOps and production-grade systems including Docker, Kubernetes, Spark, model registries, and CI / CD workflows
- Prior experience in open-source GenAI contributions, applied LLM / GenAI research, or large-scale production AI systems
- B.S. / M.S. / Ph.D. in Computer Science, Data Science, Machine Learning, or a related field.
Required :
5+ years of experience in designing, deploying, and scaling ML / DL systems in productionProficient in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAXExperience with LLM fine-tuning, LoRA / QLoRA, vector search (Weaviate / PGVector), and RAG pipelinesFamiliarity with agent-based development (e.g., ReAct agents, function-calling, orchestration)Solid understanding of MLOps : Docker, Kubernetes, Spark, model registries, and deployment workflowsStrong software engineering background with experience in testing, version control, and APIsProven ability to balance innovation with scalable deploymentB.S. / M.S. / Ph.D. in Computer Science, Data Science, or a related fieldRole & Responsibilities :
Looking for a Senior Data Scientist with strong expertise in AI, machine learning engineering (MLE), and generative AI. You will play a leading role in designing, deploying, and scaling production-grade ML systems - including large language model (LLM)-based pipelines, AI copilots, and agentic workflows. This role is ideal for someone who thrives on balancing cutting-edge research with production rigor and loves mentoring while building impact-first AI applications.
Responsibilities :
Own the full ML lifecycle : model design, training, evaluation, deploymentDesign production-ready ML pipelines with CI / CD, testing, monitoring, and drift detectionFine-tune LLMs and implement retrieval-augmented generation (RAG) pipelinesBuild agentic workflows for reasoning, planning, and decision-makingDevelop both real-time and batch inference systems using Docker, Kubernetes, and SparkLeverage state-of-the-art architectures : transformers, diffusion models, RLHF, and multimodal pipelinesCollaborate with product and engineering teams to integrate AI models into business applicationsMentor junior team members and promote MLOps, scalable architecture, and responsible AI best practices(ref : hirist.tech)