- Doctoral Degree
- Master's Degree
- Analysis Skills
- Machine Learning
We are a consulting firm specializing in technology and product development that provides engineering, research and development services to our customers. With a team of world-class engineers, scientists and project managers supported by a proven methodology in product development, we ensure predictable costs and schedules. Our customers trust us to deliver breakthrough innovations that help them create and maintain market leading positions. Join one of the most recognized teams in the electronic product development industry. We offer highly competitive compensation and benefits.
The candidate will have the opportunity to work on applied solutions where Artificial Intelligence (AI) is embedded into products to increase their performance.
The candidate will have access to a diversity of datasets, tools and frameworks required to develop algorithms and deep neural networks.
The candidate will be part of a team developing end to end AI solutions to be embedded into high performance vision sensors (synthetic image generation, image processing, deep neural network research and development, features extraction and algorithm development, inference acceleration on hardware platforms, system performances optimization and support).
Lead the development of algorithms and methods to automatically detect, classify, and track objects produced by high-performance embedded vision sensors (camera, thermal, RADAR, etc.)
Being part of a small team of engineers working in an energetic fast paced start-up environment
Must be able to complete assignments independently and on time
QUALIFICATIONS AND SKILLS
Genuinely excited and enthusiastic about learning and pushing technical limits and finding new solutions
Strong programming skills including knowledge of: Open CV, Matlab, Python, CUDA, and C++
Familiarity with NVIDA and/or INTEL hardware
Strong organizational and analytical skills
Excellent written and verbal communication skills
Attention to detail, data accuracy and quality of output
Master’s in Sciences + 5 years’ or PH.D. + 2 years’ practical experience in an Engineering field related to machine learning, deep learning, computer vision, or data science.
Practical experience in most of the following areas is required:
feature extraction and algorithm development using optical and thermal data sources
deep learning, CNN, semantic segmentation, object classification
deep learning frameworks, such as Tensor Flow, Keras, PyTorch, NVIDIA Deep Stream
classic machine learning approaches such as SVM, LDA, PCA, Naïve Bayes, k-Means, etc.
image processing, machine vision approaches
To apply, send your resume to firstname.lastname@example.org