Job Description
Overview
Voyager (94001), India, Bangalore, KarnātakaLead AI EngineerAbout Capital One
Capital One has been a pioneer through our tech journey as the first large bank to go all in on the public cloud, while operating in a complex and highly regulated business environment. We have built out a large engineering organization, moved to the cloud, re-architected our applications and data platforms, and embraced machine learning at scale. Our AI/ML capabilities are now at the forefront of what’s possible in banking.
About the Team
At Capital One India, we are committed to harnessing the power of Artificial Intelligence and Natural Language Processing to solve complex enterprise challenges. Our MLX (Machine Learning Experiences) team builds production-grade, AI-driven systems that power intelligent decision-making and automation across business functions.
About the Role
We're seeking an exceptional Lead AI/Machine Learning Engineer (Code Quality & Research) to pioneer our AI-driven code quality initiatives. This is a unique opportunity to shape the future of software engineering by building intelligent systems that elevate code quality, accelerate development velocity, and establish new standards for engineering excellence across our organization.
As a technical leader and researcher, you'll drive the development of cutting-edge LLM-powered tools for code review, test generation, and API schema validation. You'll combine deep expertise in software engineering principles with advanced machine learning to create solutions that fundamentally transform how our engineers write, review, and maintain code.
What Makes This Role Unique
This isn't just about building features, it's about advancing the state of the art in AI-assisted software engineering.
You'll have the opportunity to:
Pioneer Research: Conduct applied research in code analysis, program synthesis, and LLM applications for software engineering, with opportunities to publish and present your work
Define Standards: Establish evaluation frameworks and quality metrics that become the benchmark for LLM-driven code analysis across multiple programming languages
Drive Impact at Scale: Build systems that touch every engineer and every line of code in the organization
Lead Innovation: Shape the technical roadmap for next-generation developer experience tools
What You'll Do
Research & Innovation (40%)
Conduct cutting-edge research in LLM applications for code understanding, generation, and quality assessment
Design and implement novel evaluation frameworks for measuring code quality, test coverage, and API design across diverse programming languages (Java, Python, JavaScript, Go,
Stay at the forefront of academic and industry research in program analysis, code intelligence, and generative AI
Publish research findings through papers, technical blogs, and conference presentations
Collaborate with academic institutions and contribute to open-source projects
Technical Leadership (35%)
Architect and build production-grade ML systems for:
Intelligent code review and automated feedback
Context-aware test case generation
API schema validation and best practice recommendations
Code quality assessment and technical debt detection
Design scalable evaluation pipelines that measure model performance across coding standards, languages, and domains
Establish best practices for prompt engineering, fine-tuning, and model optimization for code-related tasks
Lead the technical design of multi-language support systems with deep understanding of language-specific idioms and patterns
Strategic Impact (25%)
Define the technical vision and roadmap for AI-powered code quality tools
Drive adoption of coding standards and quality frameworks across engineering teams
Collaborate with engineering leadership to identify high-impact opportunities
Mentor engineers and researchers, building a culture of excellence in AI and software engineering
Evangelize code quality practices and share insights through internal tech talks and documentation
Basic Qualifications
At least 7 years of software engineering experience (such as Python, GO, R, C Language, C++, Java)
At least 3 years of experience with code analysis tools and frameworks such as ESLint, SonarQube, Checkmarx
At least 2 years of experience focused on LLMs or code-based ML tasks (for example: Data handling & Preprocessing, Model Building & Training, Model Evaluation and Visualization)
At least 2 years of experience building production Machine Learning systems from research to deployment
Preferred Qualifications
Master’s or Doctoral Degree with dissertation focused on software engineering, program analysis or AI/ML applications for code
Published research papers related to Programming language theory, compilers, static analysis, Software design patterns, architectural principles, code quality metrics, Modern LLM architectures like GPT, Claude, Llama and fine-tuning techniques, evaluation methodologies for generative AI systems at top-tier conferences like ICSE, FSE, ASE, NeurIPS, ICML, ACL, EMNLP
8+ years of experience building developer tools or platforms used by large engineering organizations
6+ years of experience fine-tuning and adapting large language models for domain-specific tasks
5+ years of experience with the RAG stack for code understanding & building evaluation datasets and benchmarks for code-related tasks
4+ years of experience applying machine learning to real-world problems
3+ years of experience building Multi-modal models that combine code, documentation, and execution traces
Contributions to open-source projects in code analysis, static analysis, or developer tooling
Knowledge of DevOps, CI/CD, and integration of ML models into development workflows
At this time, Capital One will not sponsor a new applicant for employment authorization for this position.
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