Lead AI Engineer

Overview

Voyager (94001), India, Bangalore, KarnatakaLead AI Engineer

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 open source or commercial LLMs

No agencies please.