Role Description We're looking for a Senior Machine Learning Engineer with strong computer vision expertise to join our Biometrics team. You'll ramp up on the biometrics domain while contributing to the design, training, and scaling of our ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. - Design and develop computer vision models and pipelines, contributing to biometrics use cases such as face detection, quality assessment, and recognition. - Collaborate on benchmarking of models across datasets and operating conditions. - Train and optimize models using PyTorch, TensorFlow, and/or JAX. - Contribute to end-to-end ML pipelines, from data ingestion to deployment. Help design automated pipelines (Airflow) for data ingestion and cleaning. - Production Engineering: Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and support deployment on AWS. - Collaborate with and mentor ML engineers, and contribute to technical best practices across the Computer Vision team. Qualifications - 5+ years of industry experience in Machine Learning with a focus on Computer Vision (e.g., image classification, object detection, segmentation, image quality, generative models). - Strong Computer Vision fundamentals. - Awareness of algorithmic bias and willingness to learn domain-specific fairness practices. - Strong proficiency in Python (Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. - Experience designing or contributing to ML pipelines and familiarity with orchestration tools like Airflow. - Experience with GPU-based training and deploying ML services on AWS. Requirements - Research Publications in top computer vision venues (CVPR, ICCV, ECCV). - Familiarity with vector databases and ANN search. - Experience with GANs or diffusion models for data augmentation. - CoreML, LiteRT, and/or TFLite experience. - Familiarity with privacy, security, and compliance considerations in sensitive ML applications. Benefits - IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation. Company Description Jumio is a B2B technology company dedicated to eradicating online identity fraud, money laundering, and other financial crimes to help make the internet safer. We leverage AI, biometrics, machine learning, liveness detection, and automation to create solutions that are trusted by leading brands worldwide and respected by industry thought leaders. Jumio is the leading provider of online identity verification, eKYC, and AML solutions. With a global footprint, we’re expanding the team to meet strong client demand across a range of industries including Financial Services, Travel, Sharing Economy, Fintech, Gaming, and others.

Role Description Jumio is looking for a Research Engineer with a foundation in machine learning, robotics, and data infrastructure to help build and scale the systems used for data collection, model development, and product improvement. This role sits at the intersection of robotics, computer vision, and applied machine learning. You will work hands-on with robotic systems, ROS/ROS2-based modules, mobile data collection workflows, and ML pipelines that support training, evaluation, and production model performance. This is a strong opportunity for a new graduate or early-career engineer who wants to build practical systems that directly improve real-world AI products. High-quality data and reliable model evaluation infrastructure are critical to improving Jumio’s machine learning and computer vision capabilities. This role helps ensure that data collected from robotic systems and mobile applications is usable, scalable, and connected to the broader model development lifecycle. The Research Engineer will support both the robotics/data collection environment and the ML development workflow, helping the team move faster, improve model quality, and better understand model performance in production. Qualifications - Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field. - 1–2 years of relevant industry, internship, or research experience in machine learning, robotics, computer vision, or related technical areas. - Hands-on experience with ROS and/or ROS2, including building or integrating modules for robot navigation, manipulation, simulation, or data collection. - Strong foundation in machine learning fundamentals, with experience implementing models in Python using frameworks such as PyTorch, TensorFlow, scikit-learn, or similar. - Experience working with databases, writing queries, and building or maintaining data pipelines for training, testing, or evaluation. - Strong programming skills in Python and C++, with an emphasis on clean, reliable, well-documented code. - Ability to work hands-on with physical hardware, debug system behavior, and translate research or prototype work into scalable engineering solutions. Requirements - Build and integrate ROS/ROS2-based modules to support robotic navigation, manipulation, and data collection workflows. - Replicate and integrate mobile and web UI environments into robotic testing and data collection systems. - Build, maintain, and improve training and test datasets collected through robotic manipulators and in-house iOS and Android applications. - Mine, query, and analyze data from internal databases to create features, identify trends, and generate insights that improve product and model development. - Develop tools and processes to monitor data quality, model performance, and model accuracy in production environments. - Implement end-to-end machine learning workflows, including data preparation, model training, testing, evaluation, and deployment support. - Write clean, modular, well-documented C++ and Python code that can be maintained and extended by other engineers. - Collaborate cross-functionally with machine learning, engineering, product, and research teams to improve data collection, model development, and system performance. Nice to Have - Experience with robotic manipulators, mobile robot platforms, or lab-based robotic systems. - Familiarity with iOS and/or Android development, especially for hardware-integrated data collection applications. - Experience with data collection pipelines for computer vision, biometric systems, identity verification, or similar applied AI domains. - Exposure to production ML observability, model monitoring, drift detection, or data quality monitoring tools. - Familiarity with cloud platforms such as AWS, including S3, EC2, SageMaker, or similar tools for storage, compute, and model deployment. - Experience working in cross-functional environments with machine learning engineers, software engineers, researchers, and product teams. Jumio Values - 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. Company Description Jumio is a B2B technology company dedicated to eradicating online identity fraud, money laundering and other financial crimes to help make the internet safer. We leverage AI, biometrics, machine learning, liveness detection and automation to create solutions that are trusted by leading brands worldwide and respected by industry thought leaders. Jumio is the leading provider of online identity verification, eKYC and AML solutions. With a global footprint, we’re expanding the team to meet strong client demand across a range of industries including Financial Services, Travel, Sharing Economy, Fintech, Gaming, and others. Applicant Data Privacy We will only use your personal information in connection with Jumio’s application, recruitment, and hiring processes, as described in Jumio’s Applicant Privacy Notice. If you have any questions or comments, please send an email to privacy@jumio.com.

• Build systems to enable HubSpot's AI to understand complex data • Define technical direction for ML systems • Collaborate across product, engineering, and ML teams • Lead projects from development to measurable impact

• You will be part of a 35-person team of technology-driven sensor, IoT, and hardware engineers. • Together with your colleagues you will take on the following tasks: You are part of the team building a next-generation localization product with a learning map architecture. • You develop computer vision models (dataset preparation, auto-labeling, training optimization, edge/cloud deployment) and integrate visual and acoustic sensor data into the system. • You process multi-modal sensor data (images, radar, acoustics) under challenging field conditions such as jamming or sensor degradation. • You run machine learning and AI models directly on local sensors instead of on cloud servers and train models directly on edge hardware (e.g., NVIDIA Jetson). • You implement scalable models for low-latency applications. • You combine GPU-accelerated vision models (CUDA, TensorRT, DeepStream) with scalable backend services. • You work on real-time networking for highly scalable distributed systems. • Together with Sensor Fusion Engineers, MLOps, and DevOps Engineers you enable fast and secure deployments. • You monitor systems, troubleshoot incidents, and continuously improve observability.