The MatrixSpace team is inventing next-generation sensor technologies to make places safe. Incorporating intelligence into sensors improves resiliency and detection accuracy. The AI team at MatrixSpace researches and develops start-of-the-art computer vision, deep learning, graphics and data processing to deliver low-latency inferencing enable sensors to perform intelligent sensing. We develop software with 3D visualization, object mapping, tracking in temporal and spatial dimensions creating a model of surrounding environment.
Be part of a small technical team solving these exciting, challenging problems.
Key responsibilities
- Lead development and deployment of perception models to support program objectives.
- Continuously research, mature and advance efficient techniques to improve sensor fusion algorithms performing higher-level perceptive functions.
- Build new ML architectures, train and tune performance of models.
- Enhance sensor data collection, data transformation and procedures.
- Innovate ways to collect real world data, annotate and train models.
- Train and test models, document and analyze findings.
- Work with team to define, implement models and data processing.
Skills and Experience
- Experience in computer vision and deep learning projects.
- Deep expertise in deep learning techniques and algorithms.
- Expertise in ML frameworks, PyTorch, Tensorflow, Keras, NumPy, Pandas.
- Excellent programming skills in Python, c/C++.
- Experience with model pipelines automation to tune and test.
- Collecting training models with real-world data.
- Ability to understand, analyze and interpret data/results.
- Ability to analyze new problems, logically explain solutions.
- Nice to have experience in optimizing models for edge processing.
- Strong writing and oral communication skills.
Qualifications
- MS or PhD in Machine Learning, Computer Science or Engineering, Electrical Engineering, Mechanical Engineering, Mathematics.
- Passionate about collecting and analyzing real-world data.
- Location: Burlington, MA at the Northeastern University Campus.
