SafeToNet recently launched the world’s first real-time sext filtering software that safeguards children across all social networks and messaging apps. It can identify and filter inappropriate images and text and has built an intelligent keyboard that works on both iOS and Android. SafeToNet has aspirations to safeguard children from around the world and is working with a high number of mobile network operators who will sell or give the software away for free to their clients. SafeToNet is one of just 5 companies in the world to be part of the Go-Ignite accelerator programme which is a consortium of Orange, Singtel, Deutsche Telecom and Telefonica. They give access to over 1.2bn customers. The board and executive team is highly experienced and the company is well funded, with substantial support from London’s investor community (see https://techcrunch.com/2018/02/26/safetonet-demos-anti-sexting-child-safety-tool/ ).
SafeToNet has expanded, with a new office in Waterloo for our Canadian subsidiary, SafeToNet Canada. Together with the University of Ottawa’s Natural Language Processing Lab, SafeToNet Canada is focused on developing the machine learning and natural language processing capabilities necessary for identifying complex child-safety and wellness issues in user generated digital communication data. Our Waterloo office is tasked with working together with our research partners to perform R&D and to productionize the resulting tech.
Social media generates a massive volume of data about online interactions on a daily basis. Such interactions provide useful information about users’ behaviours and psychological states. SafeToNet has an AI-based engine that constantly analyzes the patterns behind human written languages and produces insights about user’s emotional and mental health. Our emerging technologies are used to promote the safety and welfare of children.
We are seeking an aspiring Data Engineer to help us create the next generation of SafeToNet technology. In this role, you will learn data engineering in a hands-on way by assisting experienced data scientists and data engineers doing R&D leading to the production of ML models. Training, testing, data gathering, data quality tests will fill up much of your work day. You will have the opportunity to contribute to R&D projects in an increasingly substantial way as your experience grows. You will need to be adaptable, quick to learn, and willing to put in the effort required to help bring a new technology to market.
The ideal candidate should have a passion for quality, attention to detail, and continuous learning. Join an interdisciplinary team of PhD-level researchers and software developers at SafeToNet!
Roles and Responsibilities:
Work with Data Scientists and Engineers on the following:
- Conduct data quality assessment tests using standard and custom statistical measures.
- Assemble big and complex datasets based on business and research requirements.
- Clean, transform, and visualize big datasets from a variety of data formats such as text, JSON, videos, and images.
- Test and optimize algorithms that are designed to work on large datasets.
- Manage the configuration, execution, and evaluation of machine learning tests.
- Analyze, interpret, and communicate results to team members as required.
- Assist in the development of efficient, scalable, and maintainable code, such as data pipelines.
- Use different techniques and tools for information retrieval, data extraction, data visualization, web-scraping, and data augmentation.
- Configure and manage machines running jobs in AWS.
- Keep data organized, documented, and secured.
- Work with different team members to ensure data delivery and consistency.
- Create ad-hoc data tools for our data scientists to ease the training and optimization of our machine learning models.
- Bachelor’s degree in Computer Science, Software Engineering, or equivalent. You will have a keen interest in AI supported by continued education and learning.
- Industry experience writing high-quality code for commercial software development projects.
- Eagerness to learn new technologies, work collaboratively, and ability to take direction from senior colleagues.
- Proficiency in Python with ability to rapidly learn ML libraries like Keras or scikit.
- Experience using machine learning and deep learning methods (demonstrated project work in deep learning on GitHub is an asset).
- Experience with big data libraries and data visualization tools.
- Experience with statistical and quantitative analysis; i.e. regression, properties of distributions, and statistical tests.
We consider it an asset if you also have any of the following:
- Direct experience with Tensorflow, Torch, or Theano libraries would be an asset
- Proficiency in source control tools such as GIT. Bitbucket and/or Github experience is an asset.
- Experience with NLP and text processing libraries such as NLTK and CoreNLP.
Why Work Here?
- Make a difference to the safety of our youth in an increasingly challenging digital age
- Flexible work hours
- Competitive wages
- Strong work-life balance
- Collaborative work environment with many talented individuals
- Centrally located in downtown Kitchener
- Close to local restaurants
- Easily accessible by public transit
How to Apply:
Candidates who are interested in applying are invited to submit their resume and cover letter, highlighting their work experiences and skills via email to email@example.com.
We thank all applicants for applying. Only selected applicants will be contacted.
SafeToNet welcomes applications from people with disabilities. Accommodations will be available on request for candidates throughout the entire recruitment and selection process.