AI/ML Developer: 4 to 7 Years

• Minimum of (2+) 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.