Machine Learning Engineer
Are you applying to the internship?
Job Description
About the Company:
Cisco ThousandEyes is a Digital Experience Assurance platform that helps organizations ensure flawless digital experiences across all networks, even those they don’t directly manage. Leveraging AI and a comprehensive collection of data from cloud, internet, and enterprise networks, ThousandEyes allows IT teams to proactively identify, diagnose, and resolve issues before they impact end-users. The platform is deeply integrated with the broader Cisco technology portfolio, enabling large-scale deployments and providing AI-driven insights across networking, security, collaboration, and observability solutions.
About the Job: Machine Learning Engineer for the Alerts Team
This role places you at the forefront of AI/ML technology and real-time data processing. As a Machine Learning Engineer, you will focus on developing and refining anomaly detection algorithms for a highly scalable stream processing platform. This position combines the challenges of managing massive datasets with the innovation of applied machine learning to deliver valuable insights to customers.
Responsibilities:
• Collaborate with a team of engineers to design, implement, and maintain large-scale AI/ML pipelines for real-time anomaly detection.
• Develop and tune machine learning models, including Deep Learning models, Machine Learning (AI/ML) Models, and Large Language Models, to detect anomalies across billions of events.
• Design and implement sophisticated anomaly detection algorithms (e.g., Isolation Forests, LSTM-based models, Variational Autoencoders) tailored to the unique characteristics of the data streams.
• Create robust evaluation frameworks and metrics to rigorously assess the performance of these algorithms.
• Implement and optimize stream processing solutions using technologies like Flink and Kafka.
• Work with exceptionally diverse and large-scale data, pushing the boundaries of real-time anomaly detection.
Qualifications:
• 3-5 years of software development experience and a minimum of 2 internships with direct experience in building and evaluating ML models and delivering large-scale ML products.
• MS or PhD in a relevant field (e.g., Computer Science, Machine Learning, Data Science).
• Proficiency in crafting machine learning models, including neural networks (transformer models, Large Language Models), decision trees, and other traditional machine learning techniques. Ability to translate concepts into working solutions.
• Fluency in machine learning frameworks such as SKLearn, XGBoost, PyTorch, or TensorFlow. Ability to utilize code strategically for innovative solutions.
• Proficiency in Python and ability to translate abstract machine learning concepts into robust, efficient, and scalable code.
• Strong Computer Science fundamentals and object-oriented design skills.
• Experience building large-scale data processing systems.
• Experience working in a fast-paced development environment.
• Strong team collaboration and communication skills.
