AI/ML Developer

You should have a minimum of 4+ years of experience in AI-based application development. Your responsibilities will include fine-tuning pre-existing models to improve performance and accuracy. You should have experience with frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar ML frameworks, as well as familiarity with APIs like OpenAI or Vertex AI. Additionally, experience with NLP tools and libraries like NLTK, SpaCy, GPT, and BERT is required. You will be implementing frameworks like LangChain, Anthropics Constitutional AI, OpenAI, Hugging Face, and Prompt Engineering techniques to build robust and scalable AI applications. Evaluating and analyzing RAG solutions and utilizing the best-in-class LLM to define customer experience solutions will be part of your role. Architecting and developing advanced generative AI solutions leveraging state-of-the-art language models (LLMs) such as GPT, LLaMA, PaLM, BLOOM, and others is also expected. You should have a strong understanding and experience with open-source multimodal LLM models to customize and create solutions. Exploring and implementing cutting-edge techniques like Few-Shot Learning, Reinforcement Learning, Multi-Task Learning, and Transfer Learning for AI model training and fine-tuning is essential. Proficiency in data preprocessing, feature engineering, and data visualization using tools like Pandas, NumPy, and Matplotlib is crucial for this role. Optimizing model performance through experimentation, hyperparameter tuning, and advanced optimization techniques is required. Proficiency in Python with the ability to get hands-on with coding at a deep level is a must. You will also be developing and maintaining APIs using Python's FastAPI, Flask, or Django for integrating AI capabilities into various systems. Having the ability to write optimized and high-performing scripts on relational databases (e.g., MySQL, PostgreSQL) or non-relational databases (e.g., MongoDB or Cassandra) is necessary. Enthusiasm for continuous learning and professional development in AI and related technologies is highly valued. Collaboration with cross-functional teams to understand business requirements and translate them into technical solutions is expected. Knowledge of cloud services like AWS, Google Cloud, or Azure is necessary. Proficiency with version control systems, especially Git, is required. Familiarity with data pre-processing techniques and pipeline development for AI model training is essential. Experience with deploying models using Docker, Kubernetes, AWS Bedrock, and Sagemaker is a plus. Strong problem-solving skills with the ability to translate complex business problems into AI solutions are crucial for success in this role.,