Deep Learning and NLP Skills:

• Proficiency in building and training deep neural networks using frameworks like TensorFlow, PyTorch, etc.
• Understanding of transformer architectures like BERT, GPT, T5, etc.
• Knowledge of sequence-to-sequence models, attention mechanisms, and embeddings.
• Experience with NLP tasks such as tokenization, named entity recognition, and sentiment analysis.

Reinforcement Learning:

• Strong understanding of the fundamentals of reinforcement learning, including concepts like Markov Decision Processes, Q-learning, and policy gradients.
• Experience with modern RL libraries like OpenAI Gym, Ray's RLlib, or Stable Baselines.
• Practical knowledge of reinforcement learning in non-stationary environments and using human feedback as rewards.

Optimization Techniques:

• Familiarity with techniques like gradient clipping, learning rate schedules, regularization, and dropout.
• Understanding of distributed training and optimization techniques to handle large datasets and models.

Computational Skills:

• Proficiency in Python and other programming languages common in the AI/ML domain.
• Knowledge of GPU and TPU computation, especially in the context of deep learning.

Research Acumen:

• Ability to read, understand, and implement findings from scientific papers, especially those related to LLMs and their optimizations.
• Contributions to the AI research community through publications, conferences, or open-source projects can be an advantage.

Deep Understanding of LLMs:

• Familiarity with the nuances of large language models, their strengths, and potential pitfalls.
• Awareness of typical business use cases for LLMs, from customer support automation to content generation.

Low-code/No-code Platform Expertise:

• Proficiency in using and configuring platforms like Langflow.
• Experience in setting up, deploying, and managing applications on such platforms.

Agent-based Modelling Skills:

• Strong understanding of defining, designing, and implementing agents, their behaviours, and interactions.
• Ability to set up policies, constraints, and orchestrate chains of agents to fulfil specific business processes or workflows.

Educational Background:

A Bachelor's or Master’s (preferably) in Computer Science, Data Science, Artificial Intelligence, or related fields.