Perception Systems: Sr. Eng. /Architect/ Team Lead - IP/CV/AI/ML/Platform/Sensor Algo./Sys. Architect

Job Description

·       The position is for an experienced computer vision engineer for conceptualization, implementation, and documentation of algorithms for vision applications on unmanned aerial systems

·       Develop high-quality, scalable code for the solutions within expected timelines and budget

·       Collaborate with cross-functional teams internally and build systems to solve real-world problems.

·       Write specification documents for imaging and video cores

·       Deal with architecture trade-offs: image quality vs. performance vs. power and area

SKILLS

·       Model properties of the camera and other sensor combinations, their calibrations, and processing elements define the architecture of a sensor pre-processing pipeline.

·       Hands-on experience in developing computer vision applications.

·       Must have worked in Optics and imaging systems.

·       Hands-on industry experience in developing real-time computer vision solutions in C/C++, C#

·       Sound mathematical approach and good understanding of linear algebra, calculus and probability theory

·       Experience in Multi-disciplinary System engineering of Data science/QA/algorithms evaluation.

·      Synthesizing physics concepts for the design of system specifications.

·       Determine SW<->HW partitioning (hard-wired accelerators vs. programmable parts)

·       Convert simulated algorithms to implementable HW variants e.g. conversion from floating point to fixed point representations

·       Close collaboration with the groups developing system software and SoCs

DESIRED PROFESSIONAL KNOWLEDGE:

The candidate is expected to be strong in ANY of the following fields mentioned below:

1.      Image processing and analysis:

a.    Spatial and frequency domain filtering

b.    Multi-resolution image processing

c.     Colour spaces

d.    Morphology

e.    Image segmentation techniques

2.     Single-view and multiple-view geometry:

a.    Camera calibration

b.    Projective geometry

c.     Feature detection and description

d.    Optical Flow

e.    Visual SLAM

f.      Object tracking

3.     Machine learning for clustering and predictions:

a.    Image/video segmentation

b.    Multi-class object detection

c.     Anomaly detection

d.    Activity recognition

e.    Neural nets / CNN

f.      Select appropriate datasets and data representation methods

g.    Extend existing ML libraries and frameworks

4.    Validation and Testing

a.    System level features

b.    Experience in Algorithm evaluation and validation processes.

c.     Validation Machine Learning based algorithms.

d.    Strong QA/QC methodology skills.

e.    Perform statistical analysis and fine-tuning using test results

f.      Train and retrain ML systems when necessary

DESIRED BEHAVIOURAL VALUES:

·       Attention to details

·       Passionate and self-motivated

·       Willingness to accept challenges

·       Respect different points of view

Skills