Posted:10 hours ago|
Platform:
On-site
Full Time
Minimum of (4+) years of experience in AI-based application development. Fine-tune pre-existing models to improve performance and accuracy. Experience with TensorFlow or PyTorch, Scikit-learn, or similar ML frameworks and familiarity with APIs like OpenAI or vertex AI Experience with NLP tools and libraries (e.g., NLTK, SpaCy, GPT, BERT). Implement frameworks like LangChain, Anthropics Constitutional AI, OpenAIs, Hugging Face, and Prompt Engineering techniques to build robust and scalable AI applications. Evaluate and analyze RAG solution and Utilise the best-in-class LLM to define customer experience solutions (Fine tune Large Language models (LLM)). Architect and develop advanced generative AI solutions leveraging state-of-the-art language models (LLMs) such as GPT, LLaMA, PaLM, BLOOM, and others. Strong understanding and experience with open-source multimodal LLM models to customize and create solutions. Explore and implement cutting-edge techniques like Few-Shot Learning, Reinforcement Learning, Multi-Task Learning, and Transfer Learning for AI model training and fine-tuning. Proficiency in data preprocessing, feature engineering, and data visualization using tools like Pandas, NumPy, and Matplotlib. Optimize model performance through experimentation, hyperparameter tuning, and advanced optimization techniques. Proficiency in Python with the ability to get hands-on with coding at a deep level. Develop and maintain APIs using Python's FastAPI, Flask, or Django for integrating AI capabilities into various systems. Ability to write optimized and high-performing scripts on relational databases (e.g., MySQL, PostgreSQL) or non-relational database (e.g., MongoDB or Cassandra) Enthusiasm for continuous learning and professional developement in AI and leated technologies. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. Knowledge of cloud services like AWS, Google Cloud, or Azure. Proficiency with version control systems, especially Git. Familiarity with data pre-processing techniques and pipeline development for Al model training. Experience with deploying models using Docker, Kubernetes Experience with AWS Bedrock, and Sagemaker is a plus Strong problem-solving skills with the ability to translate complex business problems into Al solutions.
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