Are you the one? We are looking for a Machine Learning Engineer (Computer Vision & PalmCode Algorithm) to help us push the boundaries of biometric security. You will develop and refine computer vision and ML models for presentation attack detection, contribute to the evolution of our proprietary PalmCode biometric algorithm, and design efficient models optimized to run on embedded platforms. This is a hands-on applied ML role — you’ll be working closely with our hardware and embedded teams to build small but powerful models that are accurate, secure, and performant in real-world environments. Responsibilities Develop and improve computer vision models for presentation attack detection (spoofing, fake hands, 3D prints, etc.). Enhance and optimize our PalmCode algorithm for unique biometric identification. Design and train lightweight ML models capable of running on embedded devices with limited compute resources. Collaborate with security and embedded systems engineers to integrate ML inference within trusted execution environments (TEE). Collect, clean, and curate datasets for biometric feature extraction and spoof detection. Conduct model evaluation, benchmarking, and field testing to improve robustness. Stay up to date with research in computer vision, biometric security, and efficient on-device ML. Skills Strong experience in computer vision and applied ML, ideally in biometrics, face/palm/iris recognition, or similar. Proficiency with deep learning frameworks (PyTorch, TensorFlow, ONNX). Experience building efficient models for edge/embedded deployment (quantization, pruning, distillation). Familiarity with presentation attack detection (PAD) methods and adversarial robustness. Strong programming skills in Python and C++ (experience with embedded deployment frameworks a plus). Solid grasp of ML lifecycle: data pipelines, training, evaluation, deployment. Understanding of biometric data privacy and compliance considerations. Very strong foundations in probability, statistics, linear algebra, and optimization, with the ability to reason about model behaviour beyond using existing libraries. Education & Experience Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field. 3 years of industry or academic experience applying ML/CV. Experience in biometrics or embedded ML is strongly preferred. Nice to have Experience with fine-grained recognition models (e.g., palm, fingerprint, face, voice recognition). Research or contributions in PAD or biometric security. Background in on-device inference frameworks (TensorRT, TFLite, Arm NN). Understanding of cryptography or secure ML (e.g., inference in TEE). Contributions to open-source ML/CV projects. What We Offer/ Benefits Global and Diverse Workforce: You'll work with people from various backgrounds and cultures. Learning and Development : You'll work on innovative, challenging projects and have access to experts and mentors to enhance your skills. Career Growth : Access to training, mentorship, and opportunities to contribute to open-source initiatives. Global Events and Conferences: Opportunities to attend the industry events. Collaborative and Innovative Culture: We foster teamwork and encourage new ideas. Our Commitment to Diversity At Nethermind, we celebrate diversity and are committed to creating an inclusive environment for all team members. We believe a variety of perspectives drives innovation and leads to better solutions for the blockchain community. Ready to Join Us? If you're passionate about blockchain and eager to make an impact, we’d love to hear from you. Click Apply for this job to start your journey with Nethermind.