Extreme Networks is hiring a
Sr Software Engineer-Machine Learning Platform

Summary

The job is for a Senior Software Systems Engineer specializing in Machine Learning Platform development with 5 to 12 years of experience. The role involves driving innovation, leading end-to-end software development, mentoring engineers, and upholding technical rigor. Remote or Bangalore location.

Requirements

• Degree in mathematics/computer science or related discipline
• 5+ years of experience in the complete software development lifecycle including design, coding, code reviews, testing, build processes, deployments and operations
• 5+ years of experience in programming, with proficiency in at least one programming language, preferably Python or Java
• 3+ years of experience in leading the design and architecture of large distributed systems preferably on cloud platforms (e.g., AWS, Azure, Google Cloud)
• Experience working with distributed data and ML technologies (e.g. MapReduce, Spark, Flink, Kafka, PySpark, SageMaker etc.)
• Adept at tackling highly complex, ambiguous or undefined problems

Responsibilities

• Be a thought leader and forward thinker, help drive an innovative vision for our various products and platforms, design and launch strategic machine learning (ML) solutions and drive business-wide innovation
• Take the lead in the end-to-end software development lifecycle, encompassing design, testing, deployment, and operations, lead technical discussions and strategy, and participate hands-on in design reviews, code reviews, and implementation
• Craft high-performance, production-ready machine learning code for our next-generation real-time ML platform. Extend existing ML libraries and frameworks
• Working closely with other engineers and scientists, lead solutions to accelerate model development, validation and experimentation cycles, and integrate models and algorithms in production systems at a very large scale

Preferred Qualifications

• M S or PhD in Computer Science or equivalent experience in ML
• Experience dealing with real-world large-scale datasets
• Prior experience delivering end-to-end ML solutions, including data preparation, training, fine-tuning and deployment of large models
• Prior experience in developing ML optimization techniques in frameworks like PyTorch and CUDA