
Intelligent Reasoning Expert
7 days ago
As a skilled Artificial Intelligence Engineer, you will be responsible for designing and optimizing advanced prompt engineering strategies tailored to business and domain needs.
You will fine-tune Large Language Models (LLMs) using domain-specific datasets to enhance task performance and contextual accuracy.
Additionally, you will apply Reinforcement Learning with Human Feedback (RLHF) to improve agent decision-making and behavior.
Our ideal candidate will have hands-on experience in prompt design, LLM fine-tuning, and RLHF, as well as proficiency in Python, along with TensorFlow, JAX, and PyTorch.
They will also possess knowledge of transformers, LoRA, quantization, and PEFT techniques, and the ability to design intelligent agents capable of context-aware reasoning.
We are looking for a team player who can collaborate in the design and evaluation of multi-agent architectures and workflows, and utilize A2A orchestration frameworks and MCP protocols to manage agent communication and interoperability.
The successful candidate will have a strong focus on prompt tuning, chain-of-thought prompting, and reasoning-based output generation, and be able to develop, test, and deploy ML models and agents using Python and frameworks like TensorFlow, JAX, and PyTorch.
Experience with Google Cloud AI tools, Vertex AI, PaLM, Gemini, and AutoML is highly desirable.
A prior experience deploying LLM-based applications in production, understanding of AI/ML evaluation metrics for agents and LLMs, and exposure to multi-agent systems in real-world enterprise environments are nice to have.
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