Senior Machine Learning Scientist
$159,750–$255,600 year
HybridSeattle, Washington, United States
Job Summary
Own key technical areas across the LLM, MLLM, and Computer Vision product portfolio while providing leadership to junior scientists. Research and develop cutting-edge techniques in GenAI and CV across cloud, devices, and sensors, then design and implement efficient, scalable models for multimodal data inference. Optimize algorithms for performance and energy efficiency on resource-constrained hardware by collaborating with firmware and hardware engineers. Evaluate model performance using real-world datasets and contribute to patent disclosures, academic publications, and technical documentation. Stay current with research trends to integrate findings into projects and drive the ML development lifecycle from dataset shaping to end-to-end pipeline implementation.
Required Qualifications
- 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, Computer Vision, GenAI
- Proven track record of research excellence in LLM, MLLM, Computer Vision, Robotics Perception, GenAI, demonstrated through publications in top-tier conferences or journals
- Strong proficiency in programming languages such as Python, C/C++, experience with deep learning frameworks such as TensorFlow, PyTorch, 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 computer vision 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
- Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see https://www.axon.com/company)
- US: Seattle, Boston, Scottsdale
- Location: This role is based out of our Seattle, WA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesday through Friday, with flexibility to work remotely on Mondays.
Desired Qualifications
- Experience coach and mentor junior scientists
- 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
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