Hiring: Senior AI Research Engineer Company: Cantor Fitzgerald Location: New York, NY Job Posted Time: 2026-09-13 12:53:12 Employment Type: Hybrid Target Skills & Keywords : C++, Deep Learning, Derivatives, Elasticsearch, Fine-tuning, Hugging Face, LLM, LangChain, LlamaIndex, Machine Learning, Milvus, NLP, ONNX, OpenSearch, Pinecone, Python, RAG, Systems Design, TensorRT, Transformers, Weaviate, pgvector, vLLM About the job Experience: •5+ years of professional software engineering experience, including production system design, deployment, and support. •3+ years of hands-on experience with LLMs, deep learning, NLP, or advanced AI systems. Required Skills: •FMX is seeking a Senior AI Research Engineer to help design, build, and scale Skynapse, FMX's agentic AI framework for rates and derivatives exchange workflows. •Skynapse uses a central orchestrator to understand requests, decompose work, route tasks to specialized Subject Matter Expertise agents, invoke tools, retrieve enterprise data, apply FMX domain knowledge, and synthesize responses, reports, workflow outputs, or system actions. •Design, build, evaluate, and maintain production-grade AI applications for FMX's rates and derivatives exchange business. •Develop the Skynapse orchestration layer, including task decomposition, agent routing, tool coordination, context management, response synthesis, and execution monitoring. •Evaluate when to use commercial LLM APIs, open-weight models, fine-tuned models, embedding models, rerankers, smaller specialized models, or deterministic software. •Build agentic workflows using retrieval-augmented generation, semantic search, structured outputs, function/tool calling, planning, workflow orchestration, and human review. •Integrate agents with FMX enterprise data sources, internal APIs, market data systems, reference data, documents, search indexes, and code repositories. •Design guardrails for permissions, audit logging, approval workflows, escalation paths, fallback behavior, tool-use limits, source attribution, and production kill switches. Qualifications: •Bachelor's degree in computer science, machine learning, AI, mathematics, engineering, statistics, computational linguistics, or a related technical field. •Strong academic or research background in machine learning, deep learning, NLP, transformers, LLMs, generative AI, model evaluation, or related areas. •Demonstrated understanding of transformers, attention mechanisms, tokenization, embeddings, pretraining, instruction tuning, fine-tuning, alignment, inference, context windows, decoding strategies, and evaluation. •Strong Python skills and experience writing clean, tested, maintainable, production-quality code. •Practical understanding of LLM and agent failure modes, including hallucination, prompt injection, retrieval errors, tool misuse, reasoning errors, data leakage, unsafe automation, and non-deterministic behavior. •In-depth knowledge of enterprise security, privacy, access control, entitlementing, auditability, and responsible AI considerations. •Demonstrated capacity to communicate complex AI concepts clearly and drive projects from concept through production deployment. •Master's degree or PhD in computer science, machine learning, AI, NLP, statistics, mathematics, engineering, or a related field. •Research experience or publications in LLMs, transformers, NLP, deep learning, retrieval, alignment, inference optimization, model evaluation, or agentic AI systems. •Applied hands-on capability in supervised fine-tuning, instruction tuning, LoRA, QLoRA, parameter-efficient fine-tuning, preference optimization, distillation, quantization, or domain adaptation. Compensation: •$400,000 - $500,000 / year Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!