Distributed System engineer-MTS

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We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place.

• Work with cross functional team members to define, design, implement, deploy and support features for machine learning and rule-based detections.
• Build and maintain scalable and reliable infrastructure for model lifecycle management, and deployment using cloud platforms and containerization technologies.
• Contribute to the development of tools, frameworks, and libraries to streamline detection workflows and improve productivity
• Continuously raise standard of engineering excellence by implementing best practices for development,testing, and deployment
• Operate in an Agile environment and participate in all phases of software development.

• Education: Bachelor or Master’s degree in Computer Sciences or equivalent field
• Industry Experience: 2-4 years including

• Experience in designing, implementing and operating large scale distributed systems in public cloud environments (AWS, GCP or Azure)
• Experience with Containers and orchestration technologies (e.g. Docker, Kubernetes)
• Familiarity with DevOps practices, CI/CD tools, Configuration management and Infrastructure as a code (IaC)

• Programming: Proficiency in object-oriented and multi-threaded programming in Java and/or Python
• Software Design: Demonstrable understanding of design patterns, distributed systems, data structures and algorithms
• Operating System: Development and software management on Linux (e.g., CentOS, RHEL) and Windows
• Agile: Experience with Agile development methodology
• Communication: Excellent oral and written communication skills
• Team: Work as a team player and value team success beyond personal contributions
• Strong debugging and troubleshooting skills

• MLOps: Previous experience in MLOps and familiarity with machine learning frameworks (like Kubeflow, MLFlow, Airflow etc.) and libraries (e.g., TensorFlow, PyTorch, scikit-learn)
• Security: Strong fundamentals knowledge in security concepts: authentication/authorization frameworks (e.g., SSO, SAML, Oauth), secure transport (e.g., SSL, TLS), identity management (e.g., certificates, PKI)
• Platform development: Proven track of designing and coding large-scale PaaS or IaaS systems.
• Big Data: Proficiency and experience with relational and NoSQL databases, message queues (Kafka, SNS/SQS, etc), Splunk and other components in data pipelines

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