AIML Engineer (GenAI), G&A Solutions Engineering (GSE)

Imagine what you could do here. At Apple great ideas have a way of becoming great products services and customer experiences very quickly. Bring passion and dedication to your job and theres no telling what you could accomplish. The Gu0026A Solutions Engineering organization at Apple primarily focuses on creative ways to engineer business solutions to meet growing needs of Apples Finance iTunes Sales Retail and Services organizations. At core our portfolio comprises of engineered custom solutions to process high volume transactions from Apple Pay iTunes Ads App Store iPhone Activations to Sales from Retail Online and Resellers. These solutions are based on cutting edge enterprise technologies ranging from Distributed Systems Microservices Java Spring/Boot Oracle MongoDB AWS services to AI/ML Generative AI and Blockchain. Accurately processing such high volume transactions is our core strength.n

The iRecon Payments team is seeking a highly motivated AI/ML Engineer to help build our next-generation payments this role you will blend classical ML with cutting-edge Generative and Agentic AI to transform how we process transactional data at scale. n

You will act as a technical catalyst modernizing complex product architectures to enable full observability and autonomous workflows for reconciliation invoicing and paymentsnnWe are looking for a self-starter who can navigate the intersection of financial data and Large Language Models to drive productivity and operational efficiencyn

2 years of experience building machine learning solutions using supervised/unsupervised learning classification recommendation systems and clustering algorithmsnnIn-depth knowledge of transformer architecture LLMs and Agentic AI conceptsnnHands-on experience fine-tuning Large Language Models (LLMs) using PEFT/LoRA for domain-specific tasksnnProven experience building and extending RAG MCP (Model Context Protocol) or multi-agent frameworks (e.g. LangChain LlamaIndex AutoGen)nnBachelors degree in Computer Science AI Machine Learning or relevant work experiencen

3 years deploying production-grade AI/ML solutions in the FinTech domainnn2 years building conversational assistants or autonomous agents using advanced techniques (LangGraph CrewAI A2A CoT ReAct Reflection)nnExperience with the full LLM lifecycle including pre-training SFT and Reinforcement Learning techniques (RLHF PPO GRPO)nnDemonstrated ability to quickly master emerging AI tools and integrate them into legacy stacksnnStrong written and verbal communication skills with the ability to explain complex AI concepts to business stakeholders