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Capital OnePosted 1 month ago

Senior Lead AI Engineer (MLXT)

$229,900–$262,400 year

On-siteNew York City, New York, United States or San Francisco, California, United States

Full TimeSenior LevelEnterprise

Job Summary

Modernize the Analyst & AIML workflow orchestration layer and UI by integrating frontier generative AI capabilities and self-serve tooling for governed, low-code/no-code model development. Build reliable, scalable, secure agentic-driven infrastructure that adheres to enterprise guardrails while scaling enterprise-grade managed AutoML offerings for tabular and time-series data. Engineer cutting-edge, automated governance frameworks within the core component marketplace to support business domain experts. Drive critical technical initiatives that shape the future of enterprise AIML infrastructure in a highly regulated environment, modernizing core platforms to reduce solution time-to-market from weeks to days.

Required Qualifications

  • Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields
  • At least 6 years of experience developing AI and ML algorithms or technologies
  • Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields
  • At least 4 years of experience developing AI and ML algorithms or technologies

Desired Qualifications

  • 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
  • Experience designing, developing, integrating, delivering, and supporting complex AI systems
  • Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders
  • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
  • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
  • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production
  • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers

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