Lead Machine Learning Engineer

Voyager , India, Bangalore, Karnataka

Lead Machine Learning Engineer

*Lead Machine Learning Engineer (Gen AI)
Generative AI Observability & Governance for ML Platform
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're looking for a
Lead ML Engineer
to join the
Machine Learning Experience (MLX) team

As a Capital One
Lead Engineer, MLE
, you'll 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 genAI 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'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.
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, or related field.
• Atleast 7 years of experience in machine learning engineering, building data intensive solutions using distributed computing.
• 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.
• Experience with cloud platforms like AWS, Azure, or GCP.
• Atleast 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, or a similar field.
• Experience in machine learning, particularly in deploying and operationalizing ML models.
• 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.

No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. 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 ; 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.

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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).