Machine Learning Engineer - Video
Muse is creating an advanced AI to search the world's video. We are looking for engineers who want to be at the forefront of search and discovery to make searching video as intuitive as recalling a memory in your mind. We are working across the frontiers of storage & distributed file systems, machine learning infrastructure, high performance computing and intuitive user interfaces across (web, mobile, voice and beyond).
You will join the machine learning team in sunny Lisbon with a focus on implementing and productionizing the latest machine learning algorithms to analyze video and interpret the knowledge inside video across speech, people, objects, actions and locations.
We are agnostic to the algorithms, but care deeply about the computational efficiency of these algorithms in the analysis of a video file.
- Drive the research and implemention of APIs to analyze speech, sound, vision, and motion in video enabling new capabilities in our product
- Drive the research and implementation of systems where humans contribute data to improve these algorithms (e.g reinforcement learning based tagging, clustering-labelling, or evolutionary data capture systems)
- Debug these algorithms across accuracy/computational performance and continue to improve them with a strong cadence of improvements
- Create production ready microservices that can be implemented across our product prototyping algorithms in python and eventually implementing in C/C++
- Research background (PhD/Masters) in video analysis algorithms with emphasis on deep learning
- Experience of training and constructing/tuning deep neural networks in Theano, tensorflow
- Coding fluency in Python and C/C++, and experience of Docker (if not look it up!)
- Incredible detail orientation (Garbage in, Garbage out)
- Mathematical/Statistical/CS intuition -- Physics, EE backgrounds are good!
- Passion for building the best search technology for video and being at the forefront of applying supervised and unsupervised methods of analysis of video
- Full-stack scientist - you know the drill of collecting data, cleaning data, analyzing data, prototyping analysis algorithms and profiling your work to iteratively optimize
- You like coding and can show your ideas working -- after all video is visual!
- You have very strong motivation to put your work into production and drive product development from the front
- You manage your time well, and know when to come out of rabbit holes
- You are a great communicator, and positive personality
- You take your work product seriously, but not your ego
Nice to have
- Software engineering skills outside research for fun - e.g. web/mobile
- You know how to make these algorithms work offline
- Audacious work
- Health benefits
- Food allowances