The posting, in Axon's own words
archived Sep 10, 2026Join Axon and be a Force for Good.
At Axon, we’re on a mission to Protect Life. We’re explorers, pursuing society’s most critical safety and justice issues with our ecosystem of devices and cloud software. Like our products, we work better together. We connect with candor and care, seeking out diverse perspectives from our customers, communities and each other. Life at Axon is fast-paced, challenging and meaningful. Here, you’ll take ownership and drive real change. Constantly grow as you work hard for a mission that matters at a company where you matter. Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a key member of our research and development efforts, you will play a crucial role in advancing the state-of-the-art in Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), Computer Vision and GenAI technologies for law enforcement and beyond. You will collaborate with cross-functional teams to design, develop, and deploy cutting-edge LLM, MLLM, CV models and algorithms and solutions that enable intelligent reasoning, perception and understanding of multimodal data.
What You’ll Do
Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see https://www.axon.com/company ) EU: Tampere, Finland or London, UK or Brussels, Belgium
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Responsibilities
Own one or more key technical areas across LLM, MLLM, CV product portfolio. Provide technical leadership to junior scientists, guiding the transition of R&D concepts into impactful Axon product feature. Research and develop cutting-edge techniques in LLM, MLLMs, GenAI, and Computer Vision across cloud, devices and sensors based data sources. Design and implement efficient and scalable MLLM models for inference and analysis of multimodal data. Explore novel approaches to address challenges in NLP, NLU, Object Detection, Object Recognition, Object Tracking, Segmentation, and Scene Understanding. Optimize AI models, algorithms for performance, memory footprint, and energy efficiency to meet the requirements of resource-constrained devices. Join force with MLEs or firmware or hardware engineers to leverage hardware accelerators and optimize algorithms for specific hardware architectures. Evaluate the performance of LLM, MLLM, CV models using real-world datasets and design experiments to validate their effectiveness. Stay up-to-date with the latest research trends and advancements in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant findings into our projects. Contribute to patent disclosures, academic publications, and technical documentation to share insights and findings with the broader community. Experience coach and mentor junior scientists.
What You Bring
PhD and with +5 years for ML Scientist, +8 years for Sr. ML Scientist, +10 years for Principal ML Scientist experience in Computer Science or a related field with a focus on LLM, MLLMs, , . Proven track record of research excellence in , MLLM, , Robotics Perception, , demonstrated through publications in top-tier conferences or journals. Strong proficiency in programming languages such as Python, C/C++, experience with frameworks such as , , or Keras and experience with ROS or robotic operational system. Drive one or more phases of the ML development lifecycle: shape datasets, investigate modeling approaches and architectures, train/evaluate/tune models and implement the end-to-end training pipeline. Leverage state-of-the-art research to deliver high quality models enabling multiple AI projects at scale. Contribute back to the research community via academic publications, tech blogs, open-source code and contributing to internal/external AI challenges Experience in developing algorithms for resource-constrained devices such as mobile phones, IoT devices, or embedded systems is highly desirable. Excellent problem-solving skills, analytical thinking, and the ability to work independently as well as collaboratively in a team environment. Strong communication skills and the ability to effectively present complex technical concepts to both technical and non-technical audiences.