KLA-Tencor Corporation - New College Graduate Job Opening
Computer Vision Engineer

SUMMARY: KLA-Tencor provides high speed vision inspection systems to the semiconductor industry. The software to drive these systems is large (2M+ LOC) and complex. The hardware tends to push the state of the art in sensing technology, optics (deep UV and lasers, high Strehl ratio, high magnification systems), and opto-mechanical stages.  In addition, we ship a significant high performance compute cluster with each tool.  These compute clusters run high performance (SSE vectorized, cache aware strip mined, all cores running) image processing software.  
 
We have an opening for a hands-on research scientist who will be working on developing state of the art algorithms for new markets in Computer Vision. The person will be working in KLA-Tencor’s CTO research group along with other members who have numerous years of experience in Physics, Image Processing, AI, HPC and related areas.
 

CANDIDATE BACKGROUND/REQUIREMENTS: The ideal candidate will have a PhD or MS in Computer Vision or a related area in AI, Image Processing, Machine Learning or Robotics. It is expected that the candidate has a broad ability to think from first principles while also having in depth knowledge in one of these areas. New College Graduates (experience less than 2 years since graduation) are encouraged to apply.
 
Potential areas of specialization/experience include:
 
    

*) Computer Vision, 2D & 3D object detection & recognition techniques

* ) Modern Machine learning Techniques ( SVMs, Bayesian Networks etc.)
    

*) Statistical Image Processing
    

*) Algorithm optimization (both high level and low level)
    

*) Parallel Processing
     

Candidates should be capable of evaluating different algorithmic approaches to extract information from a variety of  image and non-image data and use such information effectively in developing computer vision applications. An ability to interact with end-users with fuzzily-defined problems and help them refine their requirements and map them into cost-effective implementations would be an important plus. Candidates would interact with a team of code-optimization specialists and systems engineers to develop prototypes of actual systems and evaluate their real-world performance.
 
The ideal candidate will be able to develop algorithms at a high level (e.g. MATLAB), but have a view into possible implementations to make the systems cost-efficient. This involves understanding hardware capabilities and costs, and balancing hardware and software usage for system performance and cost optimization.