Director - Machine Learning Engineering

Overview

Voyager (94001), India, Bangalore, Karnataka

Director - Machine Learning Engineering

Director - 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 Director, 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

• 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 or a technical field

• At least 15  years of experience programming with Python, Go, Scala, or C/C++

• At least 5 years of experience designing and building and deploying enterprise AI or ML applications or platforms. 

• At least 3 years of experience implementing full lifecycle ML automation using ML Ops(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 10 years of people management experience and experience in managing managers. 

Preferred Qualifications:

• Master’s degree or PhD in Engineering, Computer Science, a related technical field, 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 and/or systems in cloud environments such as AWS, Azure, or GCP.

• Experience architecting cloud systems for security, availability, performance, scalability, and cost.

• Experience with delivering very large models through the ML Ops 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/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 AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting, advanced RAG and fine-tuning

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

Capital 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).