Job
Description
As a Senior Data Scientist specializing in Generative AI (GenAI), Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP), your role will involve designing, developing, and deploying advanced AI/ML models for real-world applications. You will work with Large Language Models (LLMs), Transformer architectures (BERT, GPT, LLaMA, etc.), Computer Vision, and Reinforcement Learning to build and optimize cutting-edge solutions. Key Responsibilities: - Design, develop, and deploy advanced AI/ML models such as LLMs, NLP pipelines, CV models, and RL algorithms. - Research, prototype, and implement solutions using transformer-based architectures like BERT, GPT, LLaMA. - Apply prompt engineering, retrieval-augmented generation (RAG), and fine-tuning/transfer learning techniques. - Utilize vector databases (Pinecone, Weaviate, FAISS, Milvus) for scalable knowledge retrieval. - Collaborate with engineering teams to integrate AI models into production using MLOps frameworks like MLflow, Kubeflow. - Deploy models on cloud platforms such as AWS SageMaker, GCP Vertex AI, and Azure ML. - Explore and leverage APIs/frameworks from Hugging Face, LangChain, LlamaIndex, OpenAI, Anthropic, Cohere, etc. - Build pipelines for data preprocessing, model training, evaluation, and monitoring. - Stay updated with the latest GenAI, ML, and DL research trends to bring innovative ideas for solving business challenges. Required Skills & Qualifications: - Proficiency in programming languages like Python, R, and SQL. - Experience with ML/DL Frameworks including PyTorch, TensorFlow, Keras, Scikit-learn, XGBoost, LightGBM. - Familiarity with GenAI/NLP Tools like Hugging Face Transformers, LangChain, LlamaIndex. - Knowledge of Vector Databases such as Pinecone, Weaviate, FAISS, Milvus. - Understanding of MLOps & Deployment tools like MLflow, Kubeflow, AWS SageMaker, GCP Vertex AI, Azure ML. - Strong grasp of AI/ML Concepts such as Generative AI, NLP, LLMs, Computer Vision, Reinforcement Learning, RAG, Prompt Engineering. - Excellent problem-solving, research, and analytical skills. - Ability to collaborate in cross-functional teams and effectively communicate complex technical concepts. Nice to Have: - Experience in fine-tuning domain-specific LLMs. - Knowledge of multi-modal models encompassing text, image, and audio. - Contributions to open-source AI/ML projects. - Published research papers or patents in the AI/ML/GenAI domain. This is a full-time position with an in-person work location. As a Senior Data Scientist specializing in Generative AI (GenAI), Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP), your role will involve designing, developing, and deploying advanced AI/ML models for real-world applications. You will work with Large Language Models (LLMs), Transformer architectures (BERT, GPT, LLaMA, etc.), Computer Vision, and Reinforcement Learning to build and optimize cutting-edge solutions. Key Responsibilities: - Design, develop, and deploy advanced AI/ML models such as LLMs, NLP pipelines, CV models, and RL algorithms. - Research, prototype, and implement solutions using transformer-based architectures like BERT, GPT, LLaMA. - Apply prompt engineering, retrieval-augmented generation (RAG), and fine-tuning/transfer learning techniques. - Utilize vector databases (Pinecone, Weaviate, FAISS, Milvus) for scalable knowledge retrieval. - Collaborate with engineering teams to integrate AI models into production using MLOps frameworks like MLflow, Kubeflow. - Deploy models on cloud platforms such as AWS SageMaker, GCP Vertex AI, and Azure ML. - Explore and leverage APIs/frameworks from Hugging Face, LangChain, LlamaIndex, OpenAI, Anthropic, Cohere, etc. - Build pipelines for data preprocessing, model training, evaluation, and monitoring. - Stay updated with the latest GenAI, ML, and DL research trends to bring innovative ideas for solving business challenges. Required Skills & Qualifications: - Proficiency in programming languages like Python, R, and SQL. - Experience with ML/DL Frameworks including PyTorch, TensorFlow, Keras, Scikit-learn, XGBoost, LightGBM. - Familiarity with GenAI/NLP Tools like Hugging Face Transformers, LangChain, LlamaIndex. - Knowledge of Vector Databases such as Pinecone, Weaviate, FAISS, Milvus. - Understanding of MLOps & Deployment tools like MLflow, Kubeflow, AWS SageMaker, GCP Vertex AI, Azure ML. - Strong grasp of AI/ML Concepts such as Generative AI, NLP, LLMs, Computer Vision, Reinforcement Learning, RAG, Prompt Engineering. - Excellent problem-solving, research, and analytical skills. - Ability to collaborate in cross-functional teams and effectively communicate complex technical concepts. Nice to Have: - Experience in fine-tuning domain-specific LLMs. - Knowledge of multi-modal models encompassing text, image, and audio. - Contributions to open-source AI/ML projects. - Published research papers or patents in the AI/ML/GenAI domain. This is a full
