Applied Scientist 3

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