Are you excited about developing state-of-the-art Machine Learning, Deep Learning and Natural Language Processing algorithms and designs using large data sets to solve real world problems? Do you have proven analytical capabilities and can multi-task and thrive in a fast-paced environment?
You enjoy the prospect of solving real-world problems that, quite frankly, have not been solved at scale anywhere before. Along the way, you'll get opportunities to be a fearless disruptor, prolific innovator, and a reputed problem solversomeone who truly enables machine learning to create significant impacts.
As a Senior Applied Scientist, you will bring statistical modeling and machine learning advancements to data analytics for customer-facing solutions in complex industrial settings. You will be working in a fast-paced, cross-disciplinary team of researchers who are leaders in the field. You will take on challenging problems, distill real requirements, and then deliver solutions that either leverage existing academic and industrial research, or utilize your own out-of-the-box pragmatic thinking. In addition to coming up with novel solutions and prototypes, you may even need to deliver these to production in customer facing products
- PhD degree with 4 years of applied research experience or a Masters degree and 6+ years of experience of applied research experience
- 3+ years of experience in building machine learning models for business application
- Experience programming in Java, C++, Python or related language
- Expertise on a broad set of ML approaches and techniques, ranging from supervised to unsupervised learning including SVM, RDF & DNN.
- A track record of thoughtful leadership and contributions that have advanced the field (Published in top tier conferences in the field of Machine Learning, Multimodal, NLP)
- Expertise in Deep Learning Framework (MXNet, Tensor Flow, etc.).
- Experience of deploying deep learning algorithms on edge devices.
- Experience working effectively with science, data processing, and software engineering teams
- Strong communication and data presentation skill.
- Strong personal interest in learning, researching, and creating new technologies with high commercial impact.