HummingBird - Total Talent Workforce Platform
Website:
talenttotal.org
Company:
https://www.linkedin.com/company/hummingbird-total-talent-workforce-platform
Seniority: Entry level
Industries: Software Development
Job details:
Company Description HummingBird is a Responsible AI-powered total talent workforce platform that transforms how organizations attract, engage, and retain talent through personalized, data-driven experiences. The platform optimizes every stage of the talent lifecycle—from sourcing and engagement to hiring and retention—using cutting-edge AI to improve efficiency and outcomes for both candidates and employers. Key capabilities include AI-generated job descriptions, advanced candidate matching, intelligent analysis, automated pre-screening interviews, and robust analytics with customizable reporting. HummingBird offers extensive integrations with major VMS/ATS systems, predictive insights, referral tracking, social sharing tools, and access to over 20 million global talents. Its unified recruitment ecosystem is designed to support strategic talent segmentation, continuous engagement, and white-labeled, brand-consistent experiences.
Role Description The MLOps Engineer will be responsible for designing, implementing, and maintaining robust machine learning pipelines that support HummingBird’s AI-driven talent platform. This full-time hybrid role is based in New Delhi, with flexibility for partial work from home. Day-to-day responsibilities include deploying and monitoring ML models in production, optimizing model performance and reliability, and collaborating with data scientists and software engineers to integrate AI features into the platform. The MLOps Engineer will manage CI/CD workflows for ML systems, ensure data quality and governance, and implement best practices for scalability, security, and observability. The role also involves troubleshooting production issues, improving infrastructure automation, and contributing to continuous enhancement of the platform’s AI capabilities.
Qualifications
- Candidates should possess strong Mechanical Engineering and Machine Design skills for structured problem-solving and system thinking.
- Candidates should possess Computer-Aided Design (CAD) skills to support precise modeling and documentation of complex systems and workflows.
- Candidates should possess Project Management skills to plan, coordinate, and deliver ML and infrastructure initiatives on time and within scope.
- Candidates should possess Research and Development (R&D) skills to experiment, evaluate, and improve AI/ML solutions and operational frameworks.
- Strong foundation in computer science, software engineering, or related technical discipline; a bachelor’s degree or equivalent experience is preferred.
- Experience with MLOps practices and tools (e.g., model deployment, monitoring, CI/CD pipelines, containerization, cloud platforms).
- Proficiency in scripting or programming languages commonly used in ML and DevOps (such as Python, Bash, or similar).
- Familiarity with data engineering concepts, version control, and collaborative development workflows.
- Ability to work effectively in hybrid teams, communicate complex technical concepts clearly, and document processes and systems thoroughly.
- Prior experience in AI/ML, HRTech
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