Top AI & Machine Learning Jobs

Lead design, development, deployment, and support of large-scale AI systems including foundation model training, LLM inference, similarity search, guardrails, evaluation, observability, and optimization to improve scalability, cost, latency, and throughput while guiding technical vision and cross-functional delivery.

Design, build, deploy, and maintain production ML systems and data pipelines at scale. Lead cross-functional teams to implement ML architectures, ensure model performance and governance, automate CI/CD for models, and leverage cloud platforms and ML frameworks to deliver reliable, explainable solutions.

Lead design, build, and productionize LLM and NLP solutions (RAG, embeddings, retrieval, agents). Drive model training/fine-tuning, serving, monitoring, evaluation frameworks, cost/latency optimization, and MLOps strategy for reliable, scalable AI systems.

Lead design, build, and operate scalable GenAI platform components including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Collaborate cross-functionally, invent LLM optimization techniques, and shape long-term technical vision for foundational AI systems.

Leads the design, development, deployment, and support of foundational AI systems, including model training, LLM inference, similarity search, guardrails, evaluation, governance, experimentation, and observability. Develops optimization techniques to improve scalability, latency, throughput, hardware utilization, and cost. Partners with research, engineering, product, and program teams; contributes to technical vision; and mentors engineers while applying emerging AI research in production.

Conduct applied AI research and build foundation models across design, training, evaluation, validation, and production implementation. Partner with data scientists, software engineers, machine learning engineers, and product managers to deliver scalable AI products. Research emerging methods in areas such as LLMs, optimization, behavioral models, fine-tuning, and AI safety; develop platform or solution-level code; translate complex research into business outcomes; and independently pursue impactful research agendas.

The role involves designing, developing, and supporting AI software components, leveraging various AI technologies, and optimizing performance for large-scale AI systems.

The role involves architecting a scalable AI platform, building distributed compute solutions, optimizing technologies, and mentoring internal talent in AI and ML.

As a Senior Lead AI Engineer, you will develop AI solutions, partner with cross-functional teams, optimize LLM performance, and contribute to the AI vision at Capital One.

Review and audit machine learning models and model risk practices across the enterprise. Partner with cross-functional teams to design, train, evaluate, validate, and implement ML and NLP solutions, using tools like Python, Spark, H2O, and AWS. Translate technical findings into business recommendations and assurance for stakeholders and the Audit Committee, while researching and applying emerging Generative AI and state-of-the-art methods.