Voyager (94001), India, Bangalore, Karnataka
Principal Associate Machine Learning Engineer (GEN AI)
To join the Machine Learning Experience (MLX) team!
As a Capital One Machine Learning Engineer (MLE), you'll be part of a team focusing on generative AI observability. In this role, you will work on pioneering technologies that ensure the robustness, reliability, and performance of our generative AI models. Your contributions will directly impact the scalability and success of our AI-driven products.
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're working to seamlessly infuse ML into the fabric of the company. The ML experience we're creating today is the foundation that enables each of our businesses to deliver next-generation ML-driven products and services for our customers.
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What You'll Do
- Design and implement sophisticated observability frameworks to monitor the performance and health of generative AI models.
- Build robust SDK, platform components to collect metadata, traces and parameters of models running at scale.
- Work on cutting edge LLM frameworks and their instrumentation.
- Analyze and optimize model performance, latency, and resource utilization to maintain high standards of efficiency, reliability and compliance
- Collaborate as part of a cross-functional Agile team to create and enhance software that enables state of the art, next generation big data and machine learning applications.
- Build smart products to enable actionable insights to improve model performance and scalability.
Basic Qualifications:
- Bachelor's Degree
- At least 4 years of experience designing and building NLP, LLM and DL based solutions.
- At least 4 years of experience programming with Python, Go, or Java
- At least 2 years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, CUDA, Keras, Spark, or TensorFlow.
- At least 2 years of experience in training and deploying large language or deep learning models at scale.
- At least 1 year of experience productionizing, monitoring, and maintaining GEN AI/LLM models.
- At least 1 year of experience in modern LLM orchestration and inference frameworks.
Preferred Qualifications:
- 1+ years of experience building, scaling, and optimizing ML systems.
- 2+ years of experience developing performant, resilient, and maintainable code.
- Familiarity with cloud services (AWS, GCP, Azure) and container orchestration (Kubernetes, Docker).
- Experience with model quantization or computational optimization is a plus.
No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
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.com
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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).