Artificial Intelligence/Machine Learning Engineer - LLM/Prompt Engineering

Key Responsibilities :

- Design, implement, and optimize prompt engineering strategies to elicit high-quality responses from LLMs.

- Fine-tune Google LLMs (PaLM, Gemini) using domain-specific datasets for custom use cases.

- Apply Reinforcement Learning from Human Feedback (RLHF) to improve the performance and decision-making of AI agents.

- Develop and orchestrate intelligent agents using Vertex AI Agent Builder, AutoML, and MCP (Multi-Agent Control Protocol).

- Implement Agent-to-Agent (A2A) architectures and protocols to enable seamless multi-agent collaboration.

- Contribute to the design of scalable and robust agent architectures and evaluation frameworks.

- Collaborate with cross-functional teams including data scientists, product managers, and ML researchers.

Required Skills & Qualifications :

- Deep understanding of LLM internals, including transformers, LoRA (Low-Rank Adaptation), quantization, and PEFT (Parameter-Efficient Fine-Tuning).

- Experience with Google Cloud AI ecosystem, including Vertex AI, Gemini, and AutoML.

- Practical knowledge of ADK, A2A orchestration, and MCP protocols.

- Experience in designing and optimizing chain-of-thought prompts, zero-shot, few-shot, and instruction tuning strategies.

- Strong problem-solving and algorithmic thinking skills.

Good to Have :

- Familiarity with model compression, distillation, and accelerator optimization.

- Publications or hands-on projects in natural language processing, LLM customization, or RLHF pipelines.