Senior Manager, Machine Learning Engineering

Voyager (94001), India, Bangalore, Karnataka
Senior Manager, Machine Learning Engineering
Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI.
We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
We are looking for an experienced Senior Manager, Machine Learning Engineering in MLX Platform to help us build the Model Governance and Observability systems. In this role, you will work on to build robust SDKs, platform components to collect metadata, traces and parameters of models running at scale and work on cutting edge Gen AI frameworks and their instrumentation. You will also lead the teams to analyze and optimize model performance, latency, and resource utilization to maintain high standards of efficiency, reliability and compliance. You will build and lead a highly talented software engineering team to unlock innovation, speed to market and real time processing. This leader must be a deep technical expert and thought leaders that help accelerate adoption of the engineering practices, up skill themselves with the industry innovations, trends and practices in Software Engineering and Machine Learning. Success in the role requires an innovative mind, a proven track record of delivering highly available, scalable and resilient governance and observability platforms.
What You'll Do

• Lead, manage and grow multiple teams of product focused software engineers and managers to build and scale Machine Learning Model Governance and AI Observability platforms & SDK's
• Mentor and guide professional and technical development of engineers on your team
• Work with product leaders to define the strategy, roadmap and destination architecture
• Bring a passion to stay on top of tech trends, experiment with and learn new technologies, participate in internal & external technology communities, and mentor other members of the engineering community
• Encourage innovation, implementation of state of the art ( SOTA) research technologies, inclusion, outside-of-the-box thinking, teamwork, self-organization, and diversity
• Work on cutting edge Gen AI frameworks/LLMs and provide observability using open Telemetry
• Lead the team in Search (semantic and key-word based ) and required pipelines to extract the data , ingest the data , convert into embeddings and expose the APIs
• 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.

Basic Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering
• At least 12 years of experience programming with Python, Go, Scala
• At least 5 years of experience designing, building and deploying enterprise AI or ML applications or platforms.
• At least 3 years of experience implementing full lifecycle ML automation using MLOps (scalable development to deployment of complex data science workflows)
• At least 4 years of experience leading teams developing Machine Learning solutions and scaling
• At least 8 years of people management experience and experience in managing managers.

Preferred Qualifications:

• Master's degree or PhD in Engineering, Computer Science or equivalent practical experience with a focus on modern AI techniques.
• Strong problem solving and analytical skills with the ability to work independently with ownership, and as a part of a team with a strong sense of responsibilities.
• Experience designing large-scale distributed platforms or systems in cloud environments such as AWS, Azure, GCP.
• Experience architecting cloud systems for security, availability, performance, scalability, and cost.
• Experience with delivering very large models through the MLOps life cycle from exploration to serving
• Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines.
• Experience at tech and product-driven companies or startups preferred.
• Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core platform components for Observability and Model Governance
• Experience with one or multiple areas of Gen AI technology stack including prompt engineering, guardrails, vector databases, knowledge bases, LLMs hosting, Retrieval, pre-training and fine-tuning, understanding of Observability of Gen AI stack (Agentic AI, Opensource Gen AI Observability frameworks and open Telemetry)

At this time, Capital One will not sponsor a new applicant for employment authorization for this position.
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 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.
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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).