Natural Language Processing (NLP) Engineer

Company Description HummingBird is a Responsible AI-powered total talent workforce platform that transforms how organizations attract, engage, and retain talent. The platform delivers a seamless, personalized, and data-driven experience for both candidates and employers across the entire talent lifecycle. Using cutting-edge AI, HummingBird optimizes every touchpoint from sourcing and pre-screening to hiring, analytics, and ongoing engagement. Its capabilities include intelligent candidate matching, predictive insights, configurable workflows, and deep integrations with major ATS/VMS systems, all within a white-labeled environment. With access to over 20 million global talents and robust reporting, HummingBird enables organizations to make faster, smarter, and more equitable talent decisions.

Role Description As an NLP Engineer at HummingBird, you will design, develop, and optimize natural language processing models that power candidate analysis, matching, and conversational experiences within the platform. You will work closely with product and engineering teams to build and refine algorithms for job description generation, automated pre-screening interviews, and talent segmentation, ensuring models are accurate, fair, and aligned with Responsible AI principles. Daily tasks include experimenting with state-of-the-art NLP architectures, cleaning and labeling text datasets, evaluating model performance, and deploying production-ready models into the unified recruitment ecosystem. You will also contribute to improving search and filtering capabilities, enhancing data-driven decision-making, and supporting continuous talent nurturing features. This is a full-time, on-site role based in Vadodara.

Qualifications

• Strong foundation in NLP and machine learning, including experience with text classification, entity recognition, language modeling, and conversational AI.
• Proficiency with relevant tools and frameworks such as Python, TensorFlow/PyTorch, Hugging Face Transformers, and common NLP libraries (e.g., spaCy, NLTK).
• Experience in data engineering for NLP, including dataset creation, cleaning, labeling, feature extraction, and performance evaluation using appropriate metrics.
• Skills in software engineering practices, including version control (Git), API development, model deployment, and integration of ML services into production systems.
• Understanding of Responsible AI principles, bias detection and mitigation in models, and privacy-aware data handling in talent or HR-tech contexts.
• Bachelor's or Master's degree in Computer Science, Data Science, Computational Linguistics, or a related field, or equivalent practical experience.
• Ability to collaborate with cross-functional teams, communicate complex technical concepts clearly, and work on-site with product and business stakeholders.
• Experience in recruitment technology, HR platforms, or enterprise SaaS products is a plus, as is familiarity with ATS/VMS integrations and analytics solutions.