- GRAMMARLY AI 200M ANDROID
- GRAMMARLY AI 200M SOFTWARE
- GRAMMARLY AI 200M CODE
With 200 million mobile sensors fueling a dataset of virtually all the mobile code in the world, the Lookout Security Cloud can identify connections that would otherwise go unseen.Our mission is to secure and empower our digital future in a privacy-focused world where mobility and cloud are essential to all we do for work and play.
GRAMMARLY AI 200M ANDROID
Stellar communication skills, able to work well with a smart, passionate, and growing teamBonus Points:PhD degree or postdoctoral assignment in the field of Machine Learning, Statistics, image recognitionExperience in computer vision, NLP, anomaly detection, neural networksExperience with mobile platforms like Android and iOSExperience with SaaS securityOpen-source contributions and participationLookout is an integrated endpoint-to-cloud cybersecurity company. Excellent time management and organizational abilities. Great communication and collaboration skills. Superb analytical and problem-solving abilities. Experience with PyTorch, or at least another major deep learning framework such as TensorFlow, MXNet. Some experience with data science tools including Python scripting, numpy, matplotlib, scikit-learn, jupyter notebooks, bash scripting, Linux environment. GRAMMARLY AI 200M SOFTWARE
An ideal candidate has strong software engineering practicesExtensive knowledge of ML techniques, frameworks, data cleaning, modelling, and software architecture. The team operates in a production setting. At least ten years of experience as a machine learning or data science or statistics with software engineering background. Keeping abreast of developments in machine learningLead by example, demonstrating software craftsmanship and best practicesMentor and lead junior developersRequirements:Strong development background in Python and working experience in JavaBachelor’s or Master’s degree in computer science, data science, mathematics, or a related field. Documenting machine learning processes. Developing ML models, ML Ops and model trainingRunning tests, performing statistical analysis, and interpreting test results. Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks. Ensuring that algorithms generate accurate user recommendations. Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models applied to device, application, network and reputational datasets. What you’ll do:Consulting with researchers, analysts and engineers to determine and refine machine learning objectives including setting and executing against roadmaps and influencing business and product strategy. A first-class machine learning engineer will be someone whose expertise translates into the enhanced performance of predictive automation. To ensure success as a Machine Learning Engineer, you should demonstrate solid data science knowledge and experience in a related ML role. 
Help us build the foundations of our Security Graph Platform, which powers our Cloud based security products and services across consumer and enterprise customers.Help us protect the world by automating the detection of threats and malware, prevent phishing attacks, and make deep discoveries in behavior analytics.You will help shape our next generation strategy and take on some of the most interesting challenges in the company and in cyber security.
As a Senior Staff Software Engineer in ML/AI, you will work with senior management to define our next generation predictive security models from the ground up.You will be evaluating existing machine learning (ML) processes, mechanisms, models, while setting direction on our next generation predictive models.We are looking for a principal machine learning engineer to optimize our existing machine learning systems, while developing our next generation models.Our extensive security datasets and data pipelines are a tremendous asset for the application of ML/AI science and a unique opportunity for the curious ML/AI engineer.Lookout has collected data from over 200M devices and analyzed more than 150M applications, which is the largest dataset on the mobile security ecosystems in the world.
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