Oracle Cloud Infrastructure (OCI) is a strategic growth area for Oracle. It is a comprehensive cloud service offering in the enterprise software industry, spanning Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). OCI is currently building a future-ready Gen2 cloud Data Science service platform. At the core of this platform, lies Cloud AI Cloud Service.
What OCI AI Cloud Services are:A set of services on public cloud, that are powered by ML and AI to meet the Enterprise modernization needs, and that work out of the box. These services and models can be easily specialized for specific customer/domain by leveragingexistingOCI services.
Key Points:Enables customers to add AI capabilities to their Apps and Workflows easily via APIs or Containers, Useable without needing to build AI expertise in-house and Covers key gaps – Decision Support, NLP, Computer Vision, for Public Clouds and Enterprise in NLU, NLP, Vision and Conversational AI.
You’re Opportunity:As we blaze the trail to provide a single collaborative ML environment for data-science professionals, we will be extremely happy to have you join us and share the very future of our Machine Learning platform - by building an AI Cloud service.
We are addressing exciting challenges at the intersection of artificial intelligence and cutting-edge cloud infrastructure. We are building cloud services in Decision Support (Anomaly Detection, Time series forecasting, Fraud detection, Content moderation, Risk prevention, predictive analytics), computer vision, natural language processing (NLP) and, speech that works out of the box for enterprises. Our product vision includes the ability for enterprises to be able to customize the services for their business and train them to specialize in their data by creating micro models that enhance the global AI models.
What You’ll Do
- Provide machine learning methodology leadership.
- Work on Decision support areas such as Anomaly Detection, Fraud Detection, Recommendation Systems, Personalizer, Content Moderation and Forecasting Analytics.
- Knowledge and work experience in Mathematical and Statistical models like State Estimation techniques, statistical risk analysis using Monte Carlo Simulation, stochastic optimization and time-series forecasting.
- Build a core model of cognitive service using various open source and machine learning principles and techniques (Deep Learning, ImageNet models, CNN, RNN, Transformer, Seq2Seq).
- Brainstorm and Design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.
- Work with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively communicating your needs and understanding theirs and address external and internal shareholder's product challenges.
- Building core of Artificial Intelligence and AI Service as Decision Support, Vision, Speech, Text, NLP, NLU, and others.
- Leverage Cloud technology – Oracle Cloud (OCI), AWS, GCP, Azure, Heroku or similar technology.
- Build models with Python and machine learning libraries (Pytorch, Tensorflow), Big Data, Hadoop, HBase, Spark, etc
- Capable of quickly becoming familiar with new approaches to Machine Learning.
- You have been exploring or working on some of the latest advancements in the deep learning space like TensorFlow.
- Master’s degree (preferred) in computer science, Statistics or Mathematics, artificial intelligence, machine learning, speech recognition, natural language processing, operations research, or related technical field.
- 3+ year for PhD, 7+ years for Masters or 10+ years of Experience designing and implementing machine learning models in production environments.
- Expert in at least one high level language such as Scala/Java/F#/C#/C++ (Java and Scala preferred)
- Working knowledge of current techniques and approaches in machine learning and statistical or mathematical models like State Estimation techniques, statistical risk analysis using Monte Carlo Simulation, stochastic optimization and time-series forecasting for Anomaly detection, Fraud detection, Risk analysis etc.
- Knowledge in algorithms like Sequential Probability ratio test, One class SVM, Fourier Transformation, Holts Winters, Seasonal Hybrid ESD, Seasonal decomposition/STL.
- Experience using ML and DL languages using Python and Java, to manipulate data and draw insights.
- Practical experience and deep knowledge in algorithms for Anomaly detection, NLP, NLU, sentiment analysis, Text to Speech, Vision, recommender systems, reinforcement learning, and another AI service.
- Practical experience in feature engineering and evaluation, automation of such tasks, model interpretation &visualization.
- Experience or willingness to learn and work in Agile and iterative development and DevOps processes.
- Strong drive to learn and master new technologies and techniques.
- Deep understanding of data structures, algorithms, and excellent problem-solving skills.
- You enjoy a fast-paced work environment.
Additional Preferred Qualifications
- Deep experience in Statistics, Mathematical models, Multivariate and Univariate Anomaly detection algorithms are all a huge plus
- Experience with Cloud Native Frameworks tools and products is a plus
- Have an Impressive portfolio on Kaggle Profile is a plus.
- Hands-on experience with horizontally scalable data stores such as Hadoop and other NoSQL technologies
Our vision is to provide an immersive AI experience on Oracle Cloud. Aggressive as it might sound, our growth journey is fueled by highly energetic, technology savvy engineers like YOU who are looking to grow with us to meet the demands of building a powerful next-generation platform. Are you ready to do something big?
Design, develop, troubleshoot and debug software programs for databases, applications, tools, networks etc.
As a member of the software engineering division, you will take an active role in the definition and evolution of standard practices and procedures. You will be responsible for defining and developing software for tasks associated with the developing, designing and debugging of software applications or operating systems.
Work is non-routine and very complex, involving the application of advanced technical/business skills in area of specialization. Leading contributor individually and as a team member, providing direction and mentoring to others. BS or MS degree or equivalent experience relevant to functional area. 7 years of software engineering or related experience.
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