Remote Software Engineer-Machine Learning Infrastructure (APAC)

Description:

• Understand Stellar Cyber’s product thoroughly
• Develop features and enhancements for Stellar Cyber’s machine learning infrastructure, covering components for data streaming, preprocessing, management, model training, and inference
• Advocate for enhancements in product quality, security, and performance
• Write code that aligns with internal standards for style, maintainability, and best practices
• Engage with large-scale data systems and infrastructure
• Solve technical challenges of moderate scope and complexity
• Collaborate with Product Management and other engineering teams to ensure high-quality standards in a fast-paced setting

Requirements:

• Bachelor’s or Master’s degree in Computer Science with a minimum of three years of software development experience, or a PhD in Computer Science with a research focus on software systems
• Profound technical expertise in networking, operating systems, cloud systems, data structures, and algorithms
• Familiarity and practical experience with distributed streaming platforms like Flink and Kafka
• Knowledge in machine learning and/or security
• Proficiency in designing and developing software systems, including distributed systems and microservices
• Over three years of experience in Python and/or Java
• Strong analytical and problem-solving capabilities
• Eagerness to stay updated with new technologies and tools
• Ability to effectively communicate through text-based mediums and document technical details concisely

Benefits:

• Opportunity to work in a fast-growing cybersecurity company with a focus on innovative technologies
• Chance to contribute to a cutting-edge Open XDR platform based on advanced ML and security technologies
• Potential for career growth and development within a dynamic team environment
• Exposure to diverse technical challenges and opportunities for learning and skill enhancement
• Competitive salary and benefits package
• Collaborative work culture with opportunities for cross-team collaboration and innovation