Capital One Lead Machine Learning Engineer 

India, Karnataka, Bengaluru 

255806977

Voyager (94001), India, Bangalore, Karnataka Lead Machine Learning Engineer

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.

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 . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.