United States onlyIntroduction:
Extreme Networks is on the cutting edge of technology, pushing boundaries and creating revolutionary networking experiences. We are seeking a versatile and innovative Machine Learning Scientist to join our Core Modelling Team. The successful candidate will work on ground-breaking projects aiming to optimize network planning, design, security, operations, and support through real-time event detection, future occurrence prediction, scenario planning, and configuration optimization.
Responsibilities
- Developing innovative machine learning models for network optimization, prediction, and troubleshooting.
- Applying expertise in Graph ML, Classic ML (regression/classification), Deep Learning, Causality, and Optimization techniques.
- Develop and utilize mathematical models to solve complex network problems.
- Conducting research to develop models and validate their feasibility, performance, and relevance.
- Ensuring interpretability and usability of the models for network optimization and troubleshooting.
- Transform validated models into modular features, ensuring they meet the set engineering criteria
- Participating in the iterative process of model development, including framing problems, developing hypotheses, designing and conducting experiments, and synthesizing findings.
- Develop and execute automated tests to ensure the quality, functionality, and compatibility of new features.
- Work closely with the Engineering Team to address any issues or concerns during the integration process.
- Communicating the progress, challenges, and needs during the model development process to the Engineering Program Manager.
Qualifications:
- 5+ years of proven experience as a Data Scientist, Machine Learning Developer or similar role. At least 2 years of experience building ML Systems.
- PhD or Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
- Solid understanding of machine learning principles, algorithms, and applications.
- Expertise in Graph ML, Classic ML (regression/classification), Deep Learning, Causality, and Optimization techniques.
- Proficiency in Python and experience with libraries such as TensorFlow, PyTorch, Scikit-learn, and Dask.
- Experience with distributed machine learning and proficiency in using Dask for parallel computing.
- Excellent understanding of data structures, data modeling.
- Excellent problem-solving skills, attention to detail, and ability to work in a team-oriented environment.
- Strong communication skills to effectively collaborate with team members and report to management.
Desired Qualities
- Experience with networks is a significant asset.
- Experience with graph databases, specifically Neo4j, for network topology and service modelling is a significant asset.
- Demonstrates a 'can-do' attitude, always seeking innovative solutions, and pushing boundaries.
- Maintains a startup mindset, thriving in a dynamic, fast-paced environment, and contributing positively to team energy.
- Understands that the goal is not to use the most complex algorithm but to bring real value to our users.
Extreme Networks, Inc. (EXTR) creates effortless networking experiences that enable all of us to advance. We push the boundaries of technology leveraging the powers of machine learning, artificial intelligence, analytics, and automation. Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions and rely on our top-rated services and support to accelerate their digital transformation efforts and deliver progress like never before. For more information, visit Extreme's website or follow us on Twitter, LinkedIn, and Facebook.
We encourage people from underrepresented groups to apply. Come Advance with us! In keeping with our values, no employee or applicant will face discrimination/harassment based on: race, color, ancestry, national origin, religion, age, gender, marital domestic partner status, sexual orientation, gender identity, disability status, or veteran status. Above and beyond discrimination/harassment based on “protected categories,” Extreme Networks also strives to prevent other, subtler forms of inappropriate behavior (e.g., stereotyping) from ever gaining a foothold in our organization. Whether blatant or hidden, barriers to success have no place at Extreme Networks.
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