Software Engineer 4 (Data Science)
Location: Sunnyale, CA (HYBRID)
This Software Engineer will be engaged in data science-related research and software application development and engineering duties related to our AI Datacenter technology and autonomous platform to provide an unprecedented visibility and operational efficiency and into the user experience. The Software Engineer will collaborate with other engineers and to build the next generation of autonomous Datacenter networks leveraging big data and predictive models. The Software Engineer will leverage the data collected from the network to empower the inference engine of our Mist platform and systems, including the Mist virtual assistant chat bot. In addition, the Software Engineer will use his/her knowledge of network communication, machine learning and software engineering to develop and implement scalable algorithms to process a large amount of streaming data to detect anomalies, predict problems, and classify them in real-time. The Software Engineer will also be responsible to develop the software and algorithms to enhance the cloud intelligent for Marvis and Apstra Cloud Services for Datacenter
Job Duties:
Design and implement machine learning solutions which require to process terabytes of streaming data to detect anomalies in DC networks of our customers, predict problems and future trends, classify them in real-time (60%)Solid statistics and math background, good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM, Decision Forests.Excellent Communication Skills to articulate observations and use cases with PM and network domain experts who are not experienced in AI/ML through data visualization tool.Have done time series data analysis, forecasting and correlation is preferrable.Have utilized latest AI/ML techniques, such as Neural Networks, Transformer, etc. for time series data or interested to explore these techniques for time series data. Analyze feature requirements from product manager, collaborate with engineers and data scientists to design the solutions.Require good understanding of datacenter networking topology and protocols.Troubleshoot production environment and customer reported issues (20%)Require the knowledge of the multi-cloud production environmentRequire the agility to troubleshoot open-source data processing engine, such as Apache Spark, Apache Storm and Apache FlinkUtilize analytical and programming skills and open-source systems, such as Hadoop, Hive, Spark, Elasticsearch, Redis, etc. develop data processing pipeline required efficacy and latency (20%) Require good knowledge and experience of the big data tool sets and techniques of distributed storage and computation engineRequire the experience to develop the reusable and highly scalable data processing componentRequire good knowledge and experience to work with cloud based CICD tools and cloud devops teams to collect stats and create monitors for our data processing pipelines
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Minimum Salary: $140,800.00
Maximum Salary:$202,400.00
The pay range for this position is expected to be between $140,800.00 and $202,400.00/year; however, the base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position also includes medical benefits, 401(k) eligibility, vacation, sick time, and parental leave. Additional details of participation in these benefit plans will be provided if an employee receives an offer of employment.
If hired, employee will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.
Juniper’s pay range data is provided in accordance with local state pay transparency regulations. Juniper may post different minimum wage ranges for permanent residency petitions pursuant to US Department of Labor requirements.