Lead Machine Learning Engineer

Overview

Voyager (94001), India, Bangalore, Karnataka

Lead Machine Learning Engineer

At Capital One India, we are committed to harnessing the power of Artificial Intelligence and Natural Language Processing (NLP) 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.

We are seeking a Lead Machine Learning Engineer - NLP to drive the development of cutting-edge NLP and AI models that enable semantic understanding, real-time inference, and contextual reasoning from structured and unstructured data. This role combines deep expertise in NLP and AI techniques with strong software engineering to deliver scalable, intelligent solutions for the enterprise.

What You’ll Do:

• Lead the design and development of advanced NLP and AI models for enterprise-grade applications.

• Build scalable machine learning pipelines for model training, evaluation, deployment, and monitoring in production environments.

• Apply techniques such as semantic parsing, text classification, summarization, retrieval-augmented generation (RAG), and knowledge graph construction.

• Leverage LLMs and transformer-based architectures (BERT, GPT, T5, etc.) to build domain-specific language models.

• Implement AI methodologies including reinforcement learning, few-shot learning, and zero-shot inference to enhance NLP models.

• Collaborate with product, engineering, and data science teams to integrate intelligent NLP capabilities into applications and platforms.

• Optimize for low-latency inference and ensure high availability of deployed models.

• Design robust evaluation metrics and feedback loops to ensure continuous learning and model performance improvements.

• Stay up to date with the latest research in NLP and AI to incorporate innovative methods into practical applications.

Required Qualifications:

• 7-10 years of experience in applied machine learning, with a strong focus on NLP and AI.

• Expertise with transformer-based models (BERT, RoBERTa, GPT, T5) and deep learning frameworks (PyTorch, TensorFlow).

• Strong programming skills in Python and experience with ML lifecycle tools such as MLflow, Airflow, or Kubeflow.

• Proven experience in deploying and scaling NLP models in production environments.

• Deep understanding of NLP tasks including NER, intent classification, question answering, embeddings, and entity resolution.

• Experience working with large-scale unstructured and semi-structured data sources.

• Familiarity with cloud-native ML development and MLOps best practices.

Preferred Qualifications:

• Experience integrating LLMs using fine-tuning, prompt engineering, or retrieval-augmented generation techniques.

• Knowledge of semantic search, vector similarity, embeddings stores, and knowledge graphs.

• Contributions to open-source NLP/AI libraries or publications in leading AI conferences.

• Familiarity with regulatory and ethical considerations for AI in enterprise environments.

Capital One is an equal opportunity employer committed to diversity and inclusion. If you require an accommodation during the hiring process, please contact our recruiting team.

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).