Machine Learning Engineer (AI Agents)

• Design, fine-tune, and optimize large language models (LLMs) for specific use cases and domains
• Develop and implement prompt engineering techniques to enhance model capabilities and performance
• Create autonomous AI agents capable of performing complex tasks through language understanding and reasoning
• Build retrieval-augmented generation (RAG) systems that combine LLMs with external knowledge sources
• Implement evaluation frameworks to benchmark LLM and agent performance across various metrics
• Optimize models for production deployment with attention to latency, throughput, and cost
• Design conversational flows and dialogue management systems for AI assistants
• Develop techniques to ensure responsible AI deployment, including safety guardrails and bias mitigation
• Stay current with the rapidly evolving NLP/LLM research landscape and implement state-of-the-art techniques

• Strong experience with transformer-based models and frameworks (Hugging Face, PyTorch, TensorFlow)
• Practical experience fine-tuning, serving, and optimizing LLMs (e.g., GPT models, Llama, Claude, Mistral)
• Expertise in NLP techniques including prompt engineering, embeddings, and semantic search
• Experience with vector databases and retrieval systems (Pinecone, Weaviate, Faiss, etc.)
• Familiarity with model quantization, distillation, and other optimization techniques
• Experience with LLM orchestration frameworks (LangChain, LlamaIndex, etc.)
• Working knowledge of cloud platforms (AWS, GCP, Azure) for ML model deployment
• Proficiency with containerization technologies (Docker, Kubernetes)
• Strong understanding of LLM evaluation methodologies and metrics

Nice-to-Have skills:

• Experience developing multi-agent systems or agent-based architectures
• Knowledge of reinforcement learning from human feedback (RLHF) techniques
• Familiarity with LLM inference optimization (vLLM, TensorRT, ONNX)
• Experience with tools for LLM observability, evaluation, and debugging
• Experience with multimodal models combining text, vision, and audio
• Knowledge of LLM security, safety, and alignment techniques