Petabytes of visual data (images, videos) are getting captured or generated across various industries and companies increasingly want to deploy machine learning (ML) to extract business value and intelligence from this enormous collection of data. The last decade was focused on teaching computers to watch and learn. As ML deployments move to production, these efforts are getting hindered by the lack of a data management solution that recognizes the challenges and opportunities presented by the magnitude of visual data. Given that over 80% of data collected is pixel data in some form, companies across various domains are pouring billions of dollars into finding ways to exploit this data and convert it to business value. Our product, the ApertureData Platform, can manage this vast amount of visual data, regardless of the vertical it is deployed in, so that these companies can make machines learn better and focus on the way to extract business insights and value rather than worrying about data infrastructure. We accelerate AI applications by providing a Data Management platform that redefines how large visual data sets are stored, searched and processed.
ApertureData Platform, built on top of the open source Visual Data Management System, relies on the combination of a fast graph database for metadata and machine learning ready access to images, videos, and feature vectors. Our interface offers a unique and unified interface to remove complexities and ease the life of ML practitioners and data scientists from the data engineering perspective.
As an early employee at ApertureData, you will scale up our core technology and integrate with machine learning and high bandwidth data ingestion frameworks. You will have the opportunity to work with our early customers from very interesting application domains, who are themselves deploying ML in innovative application areas, and guide the future interface for our product to reflect the needs of our users. ApertureData is well positioned to be the technical leader in addressing the next generation of challenges for machine learning based applications.
“We Manage Visual Data So Companies Can Make Machines Learn Better”
The crazy part about joining an early startup growing fast is that you can choose to work on any or all of the tasks below:
- Distributed systems development to scale on-premise and in-cloud
- Cloud scaling to build an efficient and cost-effective SaaS offering
- Deep diving into setting up and optimizing deep learning pipelines for visual data
- Optimizations, scaling, computer vision/data formats
While you get the freedom to define direction and build castles on-ground for now, it comes with some requirements so we can build fast and stay focused.
- MS or PhD degree in Computer Science, or a related technical field.
- 2+ years of experience in C++
- Understand concurrency well
- Understand the effects of cache/memory/disk as they interplay with each other and processing
- Systems level data structure and algorithm effects (kernel and driver level included)
- Networking (including some notion of RDMA)
- Application integration and testing experience
- Be comfortable with Linux, C++, and Python.
If we could have it all, we would also add:
- Productivity, development, testing, and cluster management tools/frameworks/languages such as Gtest, git, Jupyter, shell scripting, OpenCV (to know how to handle some computer vision tasks), Kafka, Spark, Tensorflow/PyTorch/Caffe2, Docker, Kubernetes, Zookeeper, and just in general keep up with new technology to know when we should pay attention to something
- Some theory (and maybe practical implementation) of CAP theorem, distributed systems programming (RAFT, 2 phase commit etc)
- Knowledge of SQL programming to help with comparative analysis, R (or some plotting tool), regression testing
We realize that hiring and retaining talent requires nurturing. Our promise to you:
- Regular supply of technical challenges: We have a large system to build to accelerate an extremely dynamic and massive market. This will be the easiest promise to keep!
- Opportunities to grow, technically and personally
- An environment where you can speak your mind and be how you like to be.
- And of course, well-stocked high-quality snacks and drinks, including some amazing coffee and chocolates: because happy engineers solve big challenges in short time.