Job
Description
Job Title: Data Scientist We are looking for an experienced Data Scientist with a strong background in Python programming, Natural Language Processing (NLP), Cognitive Neuroscience (CNS), Machine Learning (ML), and Artificial Intelligence (AI). The ideal candidate will also have a good understanding of Computer Vision (CV). You will work on developing advanced models, algorithms, and data-driven solutions for our cutting-edge products and research initiatives. This is an excellent opportunity to work with an innovative team that is shaping the future of AI. Experience:- Strong hands-on experience with Python and its libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch, etc.). Extensive experience in Natural Language Processing (NLP), including text classification, Named Entity Recognition (NER), sentiment analysis, etc. Solid understanding of Machine Learning algorithms, frameworks, and techniques (e.g., decision trees, neural networks, deep learning). Strong expertise in Artificial Intelligence (AI) and knowledge of advanced ML models such as reinforcement learning, generative models, etc. Experience in Cognitive Neuroscience (CNS) or related domains, with the ability to integrate biological concepts into machine learning tasks. Computer Vision experience is a plusability to work with image data, implement algorithms for image recognition, object detection, or segmentation. Technical Skills: Expert knowledge of Python and relevant libraries (e.g., NLTK, SpaCy, OpenCV, TensorFlow, PyTorch). Proficiency in data processing tools like SQL and experience with big data platforms (e.g., Hadoop, Spark). Familiarity with version control systems such as Git. Role - Gen AI Experience - 6+ years Location - PAN India Skills - Gen AI, LLM, Python, AIML Technical Expertise: Proven experience in developing applications with Generative AI technologies. Strong hands-on experience with multiple LLMs (OpenAI, GPT series, Claude, PaLM, etc.). Proficiency in programming languages such as Python, JavaScript, or equivalent. Experience with libraries and frameworks like Hugging Face, LangChain, or TensorFlow. Familiarity with fine-tuning, RLHF (Reinforcement Learning with Human Feedback), and prompt optimization techniques. Cloud and DevOps Knowledge: Experience deploying AI applications on cloud platforms like AWS, GCP, or Azure. Familiarity with containerization (Docker, Kubernetes) and CI/CD pipelines.
