Data Science Lead

As a Data Science Lead specializing in AI and Generative AI Solutions, your role will involve designing, developing, and deploying production-grade AI solutions leveraging modern ML pipelines, open-source LLMs, and cloud-based data platforms. Your responsibilities will include: - Designing and implementing end-to-end ML and GenAI solutions, covering data collection, model training, deployment, and monitoring. - Building production-grade ML pipelines for data preprocessing, feature engineering, model building, validation, and performance tuning. - Developing Generative AI applications using open-source LLMs and cloud-based platforms. - Working with Computer Vision and Core ML frameworks for real-world AI use cases. - Implementing RAG architectures, fine-tuning models (OpenAI, Llama, Mistral, Hugging Face, etc.), and optimizing performance. - Creating API-based integrations for AI and Data Science applications. - Collaborating with pre-sales and solution teams to design POCs and technical proposals. - Mentoring junior data scientists and engineers. - Ensuring best practices in version control, DevOps, and model governance. Qualifications Required: - 6-10 years of total experience with strong expertise in Data Science, AI, and Generative AI. - Proven track record of deploying ML and Generative AI applications to production. - Hands-on coding experience with Python, PyTorch, TensorFlow, Spark/PySpark, SQL, and NLP frameworks. - Strong understanding of GenAI tools, RAG, and LLM fine-tuning. - Experience with OpenAI, Llama, Mistral, Hugging Face models. - Knowledge of data engineering workflows including data lakes, pipelines, and warehouses. - Familiarity with Docker, Kubernetes, and DevOps deployment pipelines. - Excellent problem-solving, analytical, and communication skills. Preferred Skills: - Hands-on experience with Azure AI, Databricks, or Google Cloud Vertex AI. - Understanding of SaaS/enterprise-grade AI architectures. - Exposure to configuration management and CI/CD automation tools.,