AI & Deep Learning Research Engineer – Relocation Opportunity

Arnia AI Research is seeking outstanding research engineers for positions in the field of deep learning.
Our R&D team focuses on applied deep learning algorithms and software in computer vision, sound, and natural language processing. Previous and ongoing projects include and are not limited to 3D face recognition, Audio-Video data augmentation (generative models), natural language understanding.

RELOCATION OPPORTUNITY

We value potential as much as experience and above all an enthusiastic attitude towards this research field. Relocation Opportunity We are looking for amazing people – people who are eager to innovate, achieve, grow and lead. We attract and retain the best talent by investing and empowering our employees to constantly develop both themselves and their careers. This is the reason why we have created, and we are offering a relocation package that can give everyone the opportunity to be part of our team.
Our relocation program gives you the opportunity to live and work in a city where our offices are, be it Bucharest or Brasov. Because we know how important it is to try a new experience, to broaden your knowledge, learn a new skill-set and work with some of the best in the industry, we will provide you with the all necessary assistance to relocate in Bucharest or Brasov and be part of Arnia’s team.
Our relocation package consists of initial accommodation expenses, real estate assistance, visa assistance (if the case), reimbursement of expenses related to physical move (packing and moving, storage, etc) and other costs related to the disruption in your life created by the move.

As a Research Engineer at Arnia, you’ll work with a talented group of software engineers and scientists to design and implement cutting edge AI technologies.

You will be part of the full R&D cycle: reading papers, prototyping algorithms, making proof of concept demonstrations. You will have the opportunity to work on advanced applied deep learning projects, implement and improve upon state-of-the-art methods, work in a team with the same interests.

You should apply if you are a software engineer who is fairly comfortable with linear algebra, basic statistics, and the basics of stochastic gradient descent. Experience in machine learning is highly valued, but we do not expect proficiency in deep learning – since the tasks we try to develop are somewhat at the edge of state-of-the-art, we trust that nobody’s an expert.

Here’s what we’d like to see in you:

• Programming skills to prototype and test ideas – proficiency in at least one programming language (C, C++, Python, MATLAB) – preferable Python
• Machine learning (Neural Networks) knowledge
• Fairly comfortable with linear algebra, calculus, statistics, and the basics of numerical optimization (stochastic gradient descent, second-order methods etc.)
• Experience with at least one main stream deep learning frameworks like TensorFlow, Caffe, Theano, PyTorch
• Know your way around a Unix shell
• Objective achievements in another field, such as creating a large software system, awards in international math/science/programming contests. (optional)

Would be a plus:

• MSc /Ph.D. in mathematics, machine learning, image or signal processing
• Track record of coming up with new ideas in machine learning (publications or projects)
• Open-source contributions to deep learning projects
• Familiarity with ARM architecture and embedded systems (mobile phones, development boards)
• Experience with high-performance computing architectures, such as FPGAs, GPUs, and DSPs