Description

At Xilinx, we are leading the industry transformation to build an adaptable, intelligent world. ARE YOU bold, collaborative, and creative? At Xilinx, we hire and develop leaders and innovators who want to revolutionize the world of technology. We believe that by embracing diverse ideas, pushing boundaries, and working together as ONEXILINX, anything is possible.

Our culture of innovation began with the invention of the Field Programmable Gate Array (FPGA), and with the 2018 introduction of our Adaptive Compute Acceleration Platform (ACAP), has made a quantum leap in capability, solidifying our role as the adaptable platform supplier of choice. From the start, we have always believed in providing inventors with products and platforms that are infinitely adaptable. From self-driving cars, to world-record genome processing, to AI and big data, to the world's first 5G networks, we empower the world's builders and visionaries whose ideas solve every day problems and enhance people's lives.

If you are PASSIONATE, ADAPTABLE, and INNOVATIVE, Xilinx is the right place for you! At Xilinx we care deeply about creating meaningful development experiences while building a strong sense of belonging and connection. We foster an environment of empowered learning, wellness, community engagement, and recognition, so you can focus on work that matters - world class technology that improves the way we live and work. We are ONEXILINX.

The successful candidate will perform groundbreaking work in machine learning methods, and tailor them to computer vision applications including object detection, segmentation, and recognition. You will work broadly across the company’s lines of business. The machine learning techniques will include feed-forward, recurrent, recursive and convolutional neural networks, as well as maximum entropy models, and other models to be developed. Responsibilities may include recruiting, hiring, and team management.

• PhD in a quantitative discipline, e.g. Computer Science, Mathematics, Operations Research, Data Science, and 8+ years of experience in a highly quantitative position.

• Experience in Deep Learning: DNN, CNN, RNN/LSTM, GAN or other auto encoder (AE).

• 5+ years of hands-on experience developing machine learning models.

• Ability to develop and debug in Python, Java, C or C++. Proficient in git version control. R and Matlab are also relevant.

• Extensive experience with machine learning APIs and computational packages (TensorFlow, Theano, PyTorch, Keras, Scikit-Learn, NumPy, SciPy, Pandas, statsmodels).

• Familiarity with basic data table operations (SQL, etc.)

• Must have the ability to design or evaluate intrinsic and extrinsic metrics of your model’s performance which are aligned with application goals.

• Must be able to effectively communicate technical concepts and results to both technical and business audiences.

Beneficial Skills

• Solid CV, time series analysis, speech recognition, or NLP background.

• Strong background in Mathematics and Statistics.

• Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal.

• Experience with GPUs and cloud-based training of deep neural networks.

• Contribution to open-source projects on Machine Learning.