Short DescriptionDesign and invent new machine learning algorithms designed to address disruptive domains, with a focus on connected homes, connected cars, IOT, and robotics. Investigate state of the art algorithms, publish high quality papers and patents.
- Work on AI solutions that are targeted towards disruptive opportunities for LG business, based on perception, computer vision, speech, audio, cyber physical systems, etc.
- Quick Proof of Concepts (POC) and project ownership around projects that need Deep Learning, Clustering/Unsupervised learning, mixed with traditional ML approaches. POCs should result in rich and deep learning experience for the organization, so that they can be applied to real world projects that are also delivered here.
- Design and invent new machine learning algorithms designed to address disruptive domains, with a focus on connected homes, connected cars, IOT, and robotics. Investigate state of the art algorithms, publish high quality papers and patents.
- AI Framework evaluation and investigation into starting a new LG AI software platform and framework for long term platform approaches.
- End to end hands-on ownership of machine learning systems deployable across various projects in SVL ‚?? including data pipelines, model generation, training data and inference engines.
- Work with other groups within LG (around AI) while maintaining clear differentiation and value in our specific offerings, and leading the path of value driven AI solutions that are innovative and deployable to real customers.
- Some amount of familiarity with system bring up, application development, and new hardware architecture is essential as we will be working across a range of new hardware (SOCs, GPUs) as part of early prototyping.
- PhD / MS (thesis option) Computer Science or Electrical Engineering focused on Machine Learning. MS or PhD with 0-3 years of experience.
- Strong background in algorithms, probability theory, abstract analysis, optimization, linear systems, machine learning, and deep learning algorithms.
- Strong publication in the broad area of machine learning demonstrating original thinking, problem solving approach and critical performance validation
- Worked on or delivered projects around Deep Learning, Machine Learning, Natural Language Processing, Computer Vision, Recommendation Systems, Pattern Recognition, Large Scale Data Mining or Artificial Intelligence.
- Applications of deep learning in one of the following areas: speech, vision, audio, NLP, or semantic analysis
- Strong Experience in one of TensorFlow, MXNet, Theano, Caffe and other open source frameworks. Solid understanding of underlying concepts of Tensor Flow (as an example) to understand/enhance the inner workings of an AI framework of choice
- Hands on coding with C/C++, Python, Lua, R, Matlab or any proficient AI language of choice
- A sense of ambition and passion to change the world using AI and Deep Learning
Sr. Artificial Intelligence Research Engineer