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Applied Scientist 3
Oracle
posted 1d ago
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Flexible timing
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Job Description
- Build and maintain scalable ML infrastructure and platforms for managing and deploying models in production environment
- Design, implement and optimize AI services / ML Engineering Platform/Infra for Data processing , Feature Engineering , Model training and Inference
- Implement best practices for ML Ops, Dev Ops including model versioning , monitoring , logging and automated testing
- Proven ability to deliver products and experience with the full software development lifecycle
- Experience working on large-scale, highly distributed services infrastructure
- Translate business needs into advanced machine learning AI services and provide strong algorithm and coding execution and delivery of Machine Learning Artificial Intelligence.
- Develop analysis and optimization methods to improve the AI platform Capabilities
- Experience working in an operational environment with mission-critical tier-one live site servicing
- Experience designing architectures that demonstrate deep technical depth in one area, or span many products, to enable high availability, scalability, market-leading features and flexibility to meet future business demands
- Stay up to date with latest advancements in machine learning , security technology and industry trends to drive innovation and maintain competitive advantage
Preferred Qualifications
- BS or MS degree in Computer Science or relevant technical field involving coding or equivalent practical experience
- 5+ years of total experience in software development
- Hands-on experience developing and maintaining services on a public cloud platform (e.g., AWS, Azure, Oracle)
- Knowledge of Infrastructure as Code (IAC) languages, preferably Terraform
- Strong proficiency in programming languages such as Python, Java and ML frameworks/libraries such as Tensor flow , Pytorch or scikit-learn
- Strong knowledge of Container and its Orchestration technology like Kubernetes, docker
- Solid understanding of software engineering principles, including version control , testing and deployment automation
- Communicate effectively to multiple stakeholders on value and insights from data
- Make Recommendations and influence the AI service roadmap for our platforms services to constantly improve Customer experience.
- Mentor other ML engineers/developer, and help them to develop their projects related to experimentation and evaluation.
- Craft a measurement strategy to evaluate the performance of complex systems against challenging requirements
- Develop robust methods for model monitoring in production and learning from feedback Ability to work with incomplete requirements and handle multiple projects with deadlines
Employment Type: Full Time, Permanent
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