Role Purpose

As an Engineering Manager at Jumio, you will lead and grow a high-performing engineering team responsible for building scalable, secure, and reliable identity verification systems. You will balance people leadership, delivery ownership, and technical direction, ensuring teams execute efficiently while maintaining high engineering standards.

You will act as a bridge between product, architecture, and engineering, enabling teams to deliver customer value while fostering a strong culture of ownership, quality, and continuous improvement.

Role Value

This role is critical to Jumio’s mission of delivering best-in-class identity verification solutions. By enabling engineers to perform at their best, driving execution discipline, and upholding technical excellence, you will directly impact delivery velocity, system reliability, and long-term platform scalability.

T-Shaped Engineering Expectation

As part of Jumio’s engineering culture, you will operate as a T-shaped engineering leader, applying deep technical judgment across the full development lifecycle. This involves active contribution to design, guiding quality/testing, driving CI/CD excellence, and ensuring scalable, reliable, and secure solutions with expertise in data modeling and advanced system patterns.

Key Responsibilities

Engineering Leadership & Delivery

• Lead one or more engineering teams, owning delivery outcomes, timelines, and quality.
• Lead technical spikes or research efforts to de-risk major architectural decisions.
• Partner with Product Managers to translate business requirements into clear technical execution plans.
• Drive sprint planning, estimation, execution, retrospectives, and post-mortems.
• Ensure predictable delivery while managing technical risk and dependencies.

People Management & Mentorship

• Hire, onboard, mentor, and develop engineers across seniority levels.
• Conduct regular 1:1s, performance reviews, and career development discussions.
• Foster a culture of accountability, psychological safety, and continuous learning.
• Support engineers in growing both technically and professionally.

Quality, Reliability & Operational Excellence

• Partner across teams to ensure high availability and performance.
• Promote strong CI/CD practices, automation, and engineering hygiene.
• Oversee production readiness, incident response, and root-cause analysis.
• Ensure teams proactively address technical debt and reliability risks.

Innovation & Tooling

• Encourage adoption of modern engineering practices, frameworks, and tooling.
• Support teams in leveraging LLMs and AI-assisted development tools to improve productivity and testing efficiency.
• Continuously evaluate ways to improve developer experience and team effectiveness.
  
  

Cross-Functional Collaboration

• Work closely with Product, Design, Security, Compliance, and other engineering teams.
• Ensure alignment across teams on priorities, dependencies, and architectural direction.
• Contribute to engineering documentation, standards, and knowledge sharing.
  
  

Skills & Qualifications

Must-Have

• 10+ years of software engineering experience, with 2+ years in an engineering management role.
• Strong background in backend systems (e.g., Java, Spring Boot, microservices architecture).
• Experience leading Agile teams and managing end-to-end delivery.
• Hands-on experience with containerization (Docker), version control (Git), and Agile methodologies
• Proven ability to mentor engineers and build high-performing teams.
• Strong communication, stakeholder management, and execution skills.
• Experience with AWS cloud platform.
  
  

Nice-to-Have

• Exposure to frontend technologies (React, Angular) to support full-stack teams.
• Familiarity with DevOps practices, containerization (Docker), and IaC tools like Terraform.
• Understanding of secure coding practices and GDPR-compliant development.
• Interest or experience in integrating AI/LLM tools into engineering workflows.
  
  

@Work

You’ll be part of a collaborative, fast-paced engineering organization with the flexibility to work remotely or from our Bangalore office (Prestige Tech Park III). In this role, you’ll partner with strong engineering leaders and teams to build high-quality, impactful solutions in digital identity verification., while building teams that are proud of both what they deliver and how they deliver it.

Role Purpose

At Jumio, we’re building trusted identity solutions powered by machine learning and biometrics. As a Backend Engineer, you will design and operate backend services that bring machine learning models into production. You’ll work closely with Machine Learning Engineers to transform models into scalable, reliable, and high-performance services running on AWS.

What You’ll Do

• Design, build, and maintain backend services for deploying and serving ML models in production

• Develop high-performance APIs and services in Java, with supporting components in Python

• Deploy and operate services on AWS using ECS + Fargate, SageMaker, or EC2 with Kubernetes

• Enable both real-time (low-latency) and batch inference workflows

• Ensure service reliability, scalability, and performance in production environments

• Implement and maintain CI/CD pipelines and deployment automation

• Monitor systems using observability tools and proactively resolve production issues

• Collaborate with ML engineers to optimize model serving and integration workflows

What We’re Looking For

• Strong backend engineering fundamentals with proficiency in Java

• Working knowledge of Python, especially in ML-related workflows

• Hands-on experience with AWS services (ECS, EC2, DynamoDB, Redis, S3, SageMaker)

• Experience with containers and orchestration (Docker, ECS, Kubernetes)

• Familiarity with Terraform or other infrastructure-as-code tools

• Experience building and operating production systems with CI/CD and monitoring

• Experience with observability tools (Datadog, New Relic, or similar)

• Understanding of how ML models are deployed and served in production

• Strong problem-solving skills and ability to work in a fast-paced environment

Nice to Have

• Experience with asynchronous programming and concurrent systems

• Familiarity with MLOps or ML platform concepts

• Experience optimizing low-latency, high-throughput systems

• Exposure to model lifecycle management (training → deployment → monitoring)

Role Purpose

We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process.

What You’ll Do

Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition)
Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions.
Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX
Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps.
Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS.
Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team.

What We’re Looking For

Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis.
Deep expertise in computer vision and biometrics, especially face recognition.
Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact.
Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code.
Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow.
Cloud Native: Hands-on experience scaling training jobs on multi-GPU clusters and deploying services on AWS (SageMaker, EC2, EKS).

Nice to Have

Research Publications: Papers in CVPR, ICCV, ECCV, or FG related to face recognition, image quality assessment, or fairness.
Large Scale Search: Experience with vector databases (e.g., Milvus, Faiss) and approximate nearest neighbor (ANN) search algorithms.
Familiarity with privacy, security, and compliance in biometric systems.
Mobile/Edge Experience: Experience porting models to edge or mobile devices utilizing frameworks such as CoreML, LiteRT, and/or TFLite.
Synthetic Data: Experience using GANs or diffusion models to generate synthetic faces for training.
Strong communication skills.

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

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• 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.

Role Purpose: The Machine Learning Engineer IV will play a critical role in advancing Jumio's Fraud team's mission to develop and enhance state-of-the-art solutions for fraud detection 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 IV at Jumio, you will have the opportunity to significantly impact the security and user experience of our ID verification solutions. Your expertise in 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

. 

• Develop, maintain, and own key fraudulent CV models of Jumio, which shapes the whole fraud product offering of Jumio. 
• Design and implement machine learning, deep learning, classical CV focused on fraud detection.
• Research to support the deployment of the advanced algorithms.
• Deploy models as AWS SageMaker endpoints or directly onto devices.
• Stay updated with the latest advancements in machine learning, deep learning, and computer vision 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 machine learning/deep learning, not including time spent studying (2 years with Master’s).
• Must have: experience with training of DL models for deepfakes, synthetic data, or gen AI data detection.
• Deep understanding of how to convert ML metrics to product goals. 
• Hands-on experience with PyTorch or TensorFlow, SKLearn, and in developing production-grade Python code.
• Demonstrated experience in implementing best practices for monitoring and maintaining ML models in production environments.
• Strong communication and problem-solving skills.

Great to have Experience and Qualifications 

• Experience in working with LLM’s or VLM’s.
• Work with image or video generation.
• Experience with cloud environments - AWS / GCP.
• Experience in working in global organizations across several timezones