Resume and JobRESUME AND JOB
Capital One logo

Lead AI Engineer

Capital One

Lead AI Engineer

full-timePosted: Jan 14, 2026

Job Description

Overview

At Capital One India, we work in a fast paced and intellectually rigorous environment to solve fundamental business problems at scale. Using advanced analytics, data science and machine learning, we derive valuable insights about product and process design, consumer behavior, regulatory and credit risk, and more from large volumes of data, and use it to build cutting edge patentable products that drive the business forward.We are looking for a Lead AI Engineer to join the Machine Learning Experience (MLX) team! As a Capital One Lead AI Engineer, you will be part of a team focusing on observability and model governance automation for cutting edge generative AI use cases. You will work on building solutions to collect metadata, metrics and insights from the large scale Gen-AI platform and build intelligent and smart solutions to derive deep insights into platform's use-cases performance and compliance with industry standards.You will contribute to building a system to do this for Capital One models, accelerating the move from fully trained models to deployable model artifacts ready to be used to fuel business decisioning and build an observability platform to monitor the models and platform components.The MLX team is at the forefront of how Capital One builds and deploys well-managed ML models and features. We onboard and educate associates on the ML platforms and products that the whole company uses. We drive new innovation and research and we are working to seamlessly infuse ML into the fabric of the company. The ML experience we are creating today is the foundation that enables each of our businesses to deliver next-generation ML-driven products and services for our customers.What You’ll Do:
  • Lead the design and implementation of observability tools and dashboards that provide actionable insights into platform performance and health

  • Leverage Generative AI models and fine tune them to enhance observability capabilities, such as anomaly detection, predictive analytics, and troubleshooting copilot

  • Build and deploy well-managed core APIs and SDKs for observability of LLMs and proprietary Gen-AI Foundation Models including training, pre-training, fine-tuning and prompting.

  • Stay abreast of the latest trends in Generative AI, platform observability, responsible AI, and drive the adoption of emerging technologies and methodologies

  • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state of the art, next generation gen-ai applications

  • Bring research mindset, lead Proof of concept to showcase capabilities of large language models in the realm of observability and governance which enables practical production solutions for improving platform users productivity.

  • Basic Qualifications:
  • Bachelor’s or Master’s degree in Computer Science, Engineering

  • At least 7 years of experience in machine learning engineering, building data intensive solutions using distributed computing

  • At least 5 years of hands-on experience with Generative AI models and their application in observability or related areas

  • At least 8 years of experience programming with Python, Go, or Java

  • At least 5 years of experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow

  • At least 5 years of experience productionizing, monitoring, and maintaining models

  • At least 5 years of experience with cloud platforms like AWS, Azure, or GCP

  • At least 7 years of experience in developing performant, resilient, and maintainable code.

  • Preferred Qualifications:
  • Master's or doctoral degree in data science/computer science, electrical engineering, mathematics

  • 8+ years of experience in machine learning, particularly in deploying and operationalizing ML models

  • 8+ years of experience building and evaluating agentic solutions

  • Familiarity with container orchestration tools like Kubernetes and Docker

  • Knowledge of data governance and compliance, particularly in the context of machine learning and AI systems

  • Prior experience in NVIDIA GPU Telemetry and experience in CUDA

  • Contributed to open source ML software

  • Authored/co-authored papers, patent on ML techniques, model, or proof of concept

  • 2+ experience in developing applications using Generative AI i.e open source or commercial LLMs

  • At this time, Capital One will not sponsor a new applicant for employment authorization for this position.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.comCapital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

    Locations

    • Bengaluru, India Bangalore, KarnātakaBengaluru

    Salary

    Estimated Salary Rangemedium confidence

    80,000 - 135,000 USD / yearly

    * This is an estimated range based on market data and may vary based on experience and qualifications.

    Skills Required

    • Python, Go, or Java programmingintermediate
    • Generative AI modelsintermediate
    • ML frameworks (scikit-learn, PyTorch, Dask, Spark, TensorFlow)intermediate
    • Cloud platforms (AWS, Azure, GCP)intermediate
    • Distributed computingintermediate
    • Model productionizing and monitoringintermediate
    • Kubernetes and Dockerintermediate
    • NVIDIA GPU Telemetry and CUDAintermediate

    Required Qualifications

    • Bachelor’s or Master’s degree in Computer Science, Engineering (experience)
    • At least 7 years of experience in machine learning engineering (experience)
    • At least 5 years of hands-on experience with Generative AI models (experience)
    • At least 8 years of experience programming with Python, Go, or Java (experience)
    • At least 5 years of experience with ML frameworks (experience)
    • At least 5 years of experience productionizing models (experience)
    • At least 5 years of experience with cloud platforms (experience)
    • Master's or doctoral degree in data science/computer science (preferred) (experience)

    Responsibilities

    • Lead design and implementation of observability tools and dashboards
    • Leverage and fine-tune Generative AI models for anomaly detection and predictive analytics
    • Build and deploy core APIs and SDKs for LLM observability
    • Stay abreast of trends in Generative AI, observability, and responsible AI
    • Collaborate in cross-functional Agile team for gen-ai applications
    • Lead Proof of Concepts for LLMs in observability and governance

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    Capital One logo

    Lead AI Engineer

    Capital One

    Lead AI Engineer

    full-timePosted: Jan 14, 2026

    Job Description

    Overview

    At Capital One India, we work in a fast paced and intellectually rigorous environment to solve fundamental business problems at scale. Using advanced analytics, data science and machine learning, we derive valuable insights about product and process design, consumer behavior, regulatory and credit risk, and more from large volumes of data, and use it to build cutting edge patentable products that drive the business forward.We are looking for a Lead AI Engineer to join the Machine Learning Experience (MLX) team! As a Capital One Lead AI Engineer, you will be part of a team focusing on observability and model governance automation for cutting edge generative AI use cases. You will work on building solutions to collect metadata, metrics and insights from the large scale Gen-AI platform and build intelligent and smart solutions to derive deep insights into platform's use-cases performance and compliance with industry standards.You will contribute to building a system to do this for Capital One models, accelerating the move from fully trained models to deployable model artifacts ready to be used to fuel business decisioning and build an observability platform to monitor the models and platform components.The MLX team is at the forefront of how Capital One builds and deploys well-managed ML models and features. We onboard and educate associates on the ML platforms and products that the whole company uses. We drive new innovation and research and we are working to seamlessly infuse ML into the fabric of the company. The ML experience we are creating today is the foundation that enables each of our businesses to deliver next-generation ML-driven products and services for our customers.What You’ll Do:
  • Lead the design and implementation of observability tools and dashboards that provide actionable insights into platform performance and health

  • Leverage Generative AI models and fine tune them to enhance observability capabilities, such as anomaly detection, predictive analytics, and troubleshooting copilot

  • Build and deploy well-managed core APIs and SDKs for observability of LLMs and proprietary Gen-AI Foundation Models including training, pre-training, fine-tuning and prompting.

  • Stay abreast of the latest trends in Generative AI, platform observability, responsible AI, and drive the adoption of emerging technologies and methodologies

  • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state of the art, next generation gen-ai applications

  • Bring research mindset, lead Proof of concept to showcase capabilities of large language models in the realm of observability and governance which enables practical production solutions for improving platform users productivity.

  • Basic Qualifications:
  • Bachelor’s or Master’s degree in Computer Science, Engineering

  • At least 7 years of experience in machine learning engineering, building data intensive solutions using distributed computing

  • At least 5 years of hands-on experience with Generative AI models and their application in observability or related areas

  • At least 8 years of experience programming with Python, Go, or Java

  • At least 5 years of experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow

  • At least 5 years of experience productionizing, monitoring, and maintaining models

  • At least 5 years of experience with cloud platforms like AWS, Azure, or GCP

  • At least 7 years of experience in developing performant, resilient, and maintainable code.

  • Preferred Qualifications:
  • Master's or doctoral degree in data science/computer science, electrical engineering, mathematics

  • 8+ years of experience in machine learning, particularly in deploying and operationalizing ML models

  • 8+ years of experience building and evaluating agentic solutions

  • Familiarity with container orchestration tools like Kubernetes and Docker

  • Knowledge of data governance and compliance, particularly in the context of machine learning and AI systems

  • Prior experience in NVIDIA GPU Telemetry and experience in CUDA

  • Contributed to open source ML software

  • Authored/co-authored papers, patent on ML techniques, model, or proof of concept

  • 2+ experience in developing applications using Generative AI i.e open source or commercial LLMs

  • At this time, Capital One will not sponsor a new applicant for employment authorization for this position.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.comCapital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

    Locations

    • Bengaluru, India Bangalore, KarnātakaBengaluru

    Salary

    Estimated Salary Rangemedium confidence

    80,000 - 135,000 USD / yearly

    * This is an estimated range based on market data and may vary based on experience and qualifications.

    Skills Required

    • Python, Go, or Java programmingintermediate
    • Generative AI modelsintermediate
    • ML frameworks (scikit-learn, PyTorch, Dask, Spark, TensorFlow)intermediate
    • Cloud platforms (AWS, Azure, GCP)intermediate
    • Distributed computingintermediate
    • Model productionizing and monitoringintermediate
    • Kubernetes and Dockerintermediate
    • NVIDIA GPU Telemetry and CUDAintermediate

    Required Qualifications

    • Bachelor’s or Master’s degree in Computer Science, Engineering (experience)
    • At least 7 years of experience in machine learning engineering (experience)
    • At least 5 years of hands-on experience with Generative AI models (experience)
    • At least 8 years of experience programming with Python, Go, or Java (experience)
    • At least 5 years of experience with ML frameworks (experience)
    • At least 5 years of experience productionizing models (experience)
    • At least 5 years of experience with cloud platforms (experience)
    • Master's or doctoral degree in data science/computer science (preferred) (experience)

    Responsibilities

    • Lead design and implementation of observability tools and dashboards
    • Leverage and fine-tune Generative AI models for anomaly detection and predictive analytics
    • Build and deploy core APIs and SDKs for LLM observability
    • Stay abreast of trends in Generative AI, observability, and responsible AI
    • Collaborate in cross-functional Agile team for gen-ai applications
    • Lead Proof of Concepts for LLMs in observability and governance

    Target Your Resume for "Lead AI Engineer" , Capital One

    Get personalized recommendations to optimize your resume specifically for Lead AI Engineer. Takes only 15 seconds!

    AI-powered keyword optimization
    Skills matching & gap analysis
    Experience alignment suggestions

    Check Your ATS Score for "Lead AI Engineer" , Capital One

    Find out how well your resume matches this job's requirements. Get comprehensive analysis including ATS compatibility, keyword matching, skill gaps, and personalized recommendations.

    ATS compatibility check
    Keyword optimization analysis
    Skill matching & gap identification
    Format & readability score
    Quiz Challenge

    Answer 10 quick questions to check your fit for Lead AI Engineer @ Capital One.

    10 Questions
    ~2 Minutes
    Instant Score

    Related Books and Jobs

    No related jobs found at the moment.