Job
Description
As an AI Application Developer, you will be responsible for fine-tuning pre-existing models to enhance performance and accuracy. Your expertise in frameworks such as TensorFlow, PyTorch, Scikit-learn, and familiarity with APIs like OpenAI or Vertex AI will be crucial. Additionally, your experience with NLP tools and libraries such as NLTK, SpaCy, GPT, and BERT will be essential for implementing robust and scalable AI applications. Your role will involve implementing frameworks like LangChain, Anthropics Constitutional AI, OpenAIs, Hugging Face, and utilizing techniques like Prompt Engineering to build advanced generative AI solutions. You will evaluate RAG solutions and leverage LLMs to define customer experience solutions effectively. Key Responsibilities: - Architect and develop advanced generative AI solutions using state-of-the-art language models (LLMs) like GPT, LLaMA, PaLM, and BLOOM. - Utilize open-source multimodal LLM models for customizing and creating solutions. - Explore cutting-edge techniques such as Few-Shot Learning, Reinforcement Learning, Multi-Task Learning, and Transfer Learning for AI model training. - Optimize model performance through experimentation, hyperparameter tuning, and advanced optimization techniques. - Develop and maintain APIs using Python's FastAPI, Flask, or Django for seamless integration of AI capabilities. - Write optimized scripts for both relational (e.g., MySQL, PostgreSQL) and non-relational databases (e.g., MongoDB, Cassandra). - Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. Qualifications Required: - Minimum of 4+ years of experience in AI-based application development. - Proficiency in Python with hands-on coding experience. - Strong understanding of data preprocessing, feature engineering, and data visualization using tools like Pandas, NumPy, and Matplotlib. - Knowledge of cloud services such as AWS, Google Cloud, or Azure. - Experience with version control systems, especially Git. - Familiarity with data pre-processing techniques and pipeline development for AI model training. - Experience with deploying models using Docker, Kubernetes. - Enthusiasm for continuous learning and professional development in AI and related technologies. This role also requires strong problem-solving skills to translate complex business problems into AI solutions effectively. Experience with AWS Bedrock and Sagemaker is a plus. As an AI Application Developer, you will be responsible for fine-tuning pre-existing models to enhance performance and accuracy. Your expertise in frameworks such as TensorFlow, PyTorch, Scikit-learn, and familiarity with APIs like OpenAI or Vertex AI will be crucial. Additionally, your experience with NLP tools and libraries such as NLTK, SpaCy, GPT, and BERT will be essential for implementing robust and scalable AI applications. Your role will involve implementing frameworks like LangChain, Anthropics Constitutional AI, OpenAIs, Hugging Face, and utilizing techniques like Prompt Engineering to build advanced generative AI solutions. You will evaluate RAG solutions and leverage LLMs to define customer experience solutions effectively. Key Responsibilities: - Architect and develop advanced generative AI solutions using state-of-the-art language models (LLMs) like GPT, LLaMA, PaLM, and BLOOM. - Utilize open-source multimodal LLM models for customizing and creating solutions. - Explore cutting-edge techniques such as Few-Shot Learning, Reinforcement Learning, Multi-Task Learning, and Transfer Learning for AI model training. - Optimize model performance through experimentation, hyperparameter tuning, and advanced optimization techniques. - Develop and maintain APIs using Python's FastAPI, Flask, or Django for seamless integration of AI capabilities. - Write optimized scripts for both relational (e.g., MySQL, PostgreSQL) and non-relational databases (e.g., MongoDB, Cassandra). - Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. Qualifications Required: - Minimum of 4+ years of experience in AI-based application development. - Proficiency in Python with hands-on coding experience. - Strong understanding of data preprocessing, feature engineering, and data visualization using tools like Pandas, NumPy, and Matplotlib. - Knowledge of cloud services such as AWS, Google Cloud, or Azure. - Experience with version control systems, especially Git. - Familiarity with data pre-processing techniques and pipeline development for AI model training. - Experience with deploying models using Docker, Kubernetes. - Enthusiasm for continuous learning and professional development in AI and related technologies. This role also requires strong problem-solving skills to translate complex business problems into AI solutions effectively. Experience with AWS Bedrock and Sagemaker is a plus.
