Senior Machine Learning Scientist II
| Company | Axon |
|---|---|
| Location | Boston, MA, USA, Seattle, WA, USA |
| Salary | $181000 – $266000 |
| Type | Full-Time |
| Degrees | PhD |
| Experience Level | Senior, Expert or higher |
Requirements
- PhD and with +8 year experience in Computer Science or a related field with a focus on MLLMs, computer vision, machine learning, or artificial intelligence.
- Proven track record of research excellence in machine learning, computer vision, robotics perception, 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.
- Excellent problem-solving skills, analytical thinking, and the ability to work autonomously as well as collaboratively in a team environment.
- Well-developed communication skills and the ability to effectively present complex technical concepts to both technical and non-technical audiences.
Responsibilities
- Own one or more key technical areas across CVML product portfolio.
- Provide technical leadership to junior scientists, guiding the transition of R&D concepts into impactful CVML product feature.
- Research and develop cutting-edge techniques in 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 visual data.
- Explore novel approaches to address challenges in object detection, recognition, tracking, segmentation, and scene understanding.
- Optimize algorithms for performance, memory footprint, and energy efficiency to meet the requirements of resource-constrained devices.
- Join forces with MLEs or firmware or hardware engineers to leverage hardware accelerators and optimize algorithms for specific hardware architectures.
- Evaluate the performance of MLLM 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.
Preferred Qualifications
- Experience in developing computer vision algorithms for resource-constrained devices such as mobile phones, IoT devices, or embedded systems is highly desirable.