Machine Learning Engineer - III (Extraction)

Jumio
BangalorePosted 7 April 2026

Job Description

Role Purpose The Machine Learning Engineer III will play a critical role in advancing Jumio's Extraction team's mission to develop and enhance state-of-the-art solutions for data extraction for ID verification purposes. This role is essential for ensuring the highest standards of security and user verification through the application of advanced machine learning and deep learning techniques, ultimately contributing to Jumio's leadership in the online identity verification, eKYC, and AML solutions market Role Value As a Machine Learning Engineer III at Jumio, you will have the opportunity to significantly impact the security and user experience of our ID verification solutions. Your expertise in machine learning, deep learning, and computer vision will drive the development of innovative algorithms that keep Jumio at the forefront of the industry. By deploying and maintaining these models in production, you will ensure the robustness and reliability of our solutions, supporting our clients across diverse industries such as Financial Services, Travel, Sharing Economy, Fintech, and Gaming. Your contributions will be pivotal in maintaining Jumio's reputation as the leading provider of online identity verification solutions, helping to meet the growing demand for secure and seamless user verification globally. Example Responsibilities . Design and implement machine learning, deep learning, classical CV and NLP algorithms focused on data extraction. Research to support the deployment of advanced algorithms. Develop, evolve, and support production-quality code. Deploy models as AWS SageMaker endpoints or directly onto devices. Stay updated with the latest advancements in deep learning, computer vision, and NLP by engaging with academic papers and attending industry conferences. Work collaboratively with other engineers and product managers in an Agile development environment. Experience and Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field. A minimum of 6+ years of commercial experience in the field of computer vision, ML or a related area, not including time spent studying (5 years with Master’s). Proficiency in computer vision, deep learning and natural language processing techniques. Proficiency in working with LLMs and VLMs. Hands-on experience with PyTorch or TensorFlow, OpenCV, SKLearn, and in developing production-grade Python code. Demonstrated experience in implementing best practices for monitoring and maintaining ML models in production environments. Experience in building, training, and deploying ML models to production environments. Strong communication and problem-solving skills. Great to have Experience and Qualifications PhD in Computer Science or related field with a specialization in computer vision, deep learning or NLP. Experience in developing algorithms for OCR, text extraction and text understanding. End to end experience (training, deploying, monitoring) with shipping VLM and LLM models in a production environment. Understanding of Spring / Java based system architectures. Experience with cloud environments - AWS / GCP. Jumio Values IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation @Work Our newest office, Jumio is in Prestige Tech Park III and growing fast. A hub of technical excellence with Machine Learning enablement at its core the engineers and team are committed to learning and innovation. They set the bar high. In a recent culture survey, these attributes were rated particularly highly in Jumio’s Indian offices. Jumio Values: IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation Equal Opportunities : Jumio is a collaboration of people with different ideas, strengths, interests and cultures. We welcome applications and colleagues from all backgrounds and of all statuses. About Jumio: Jumio is a B2B technology company dedicated to eradicating online ide ... (truncated, view full listing at source)
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