AI Engineer, FM Hosting, LLM Inference ML, AI 🏆

AI Engineer, FM Hosting, LLM Inference 💰 Salary: $229,900 - 286,200 per year At Capital One we are looking for a ML, AI engineer! 🛠️ Our tech stack: Agentic AI, AI, AWS, Azure, C#, Cloud, CUDA, Golang, Hardware, Support, Java, LLM, Machine Learning, Model Training, PyTorch, Python, Scala, Machine-Learning 📝 Rquirements: - We need a bachelors degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field, plus at least 6 years of experience developing AI and ML algorithms or technologies, or a masters degree in one of those fields plus at least 4 years of relevant experience - We need at least 6 years of programming experience with Python, Go, Scala, CUDA, or Java - We value experience leading AI system development with trade-off decisions around cost, latency, throughput, and accuracy - We prefer 7 years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or similar private cloud environments - We look for experience designing, building, delivering, and supporting complex AI systems - We value experience developing AI and ML technologies such as LLM inference, similarity search, VectorDBs, guardrails, and memory using Python, C++, C#, Java, CUDA, or Golang - We prefer experience applying advanced methods to optimize training and inference software to improve hardware utilization, latency, throughput, and cost - We look for experience building agentic AI systems and agentic workflows - We value strong communication and presentation skills, with the ability to explain complex AI concepts to peers - We prefer experience architecting and integrating heterogeneous AI systems, including rule-based, retrieval-augmented, and generative components, into unified production pipelines - We value experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes - We look for demonstrated ability to balance model performance and operating cost through dynamic inference strategies and model compression - We value experience right-sizing models, instance counts, and hardware types based on

such as context length, token inputs, and token outputs 👩‍💻👨‍💻

are: - We partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that improve how our associates work and how our customers interact with Capital One - We design, develop, test, deploy, and support AI software components, including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability - We leverage a broad stack of open-source and SaaS AI technologies, including AWS Ultraclusters, Hugging Face, VectorDBs, PyTorch, and more - We invent and introduce state-of-the-art foundation model optimization techniques to improve scalability, cost, latency, and throughput in large-scale production AI systems - We contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One - We design, implement, and optimize multi-model orchestration pipelines that integrate LLMs, vector search, and domain-specific models into unified systems - We establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency - We lead team design councils or design review boards to maintain technical consistency and compliance with AI engineering standards - We mentor Principal- and Manager-level AI engineers, encouraging cross-domain learning and raising the organizations technical maturity View this job and over 500 other transparent jobs with salaries (💰💰💰) & tech stacks (🛠️) on DevITJobs Category: ML, AI Developer / Engineer Location address: Capital One Drive 1680, Arlington, United States Salary: $229,900 - 286,200 per year