Principal Machine Learning Engineer

Website PaloAltoNtwks Palo Alto Networks


Palo Alto Networks® is the fastest-growing security company in history. We foster a culture of innovation, authenticity, and collaboration. This focus helps to advance our mission of protecting our way of life in the digital age. Our people make this possible. It’s in our everyday interactions, how we work together and treat each other, that sets Palo Alto Networks apart from other organizations. If you are a motivated, intelligent, creative, and hardworking individual, then this job is for you!


The ML Engineer is responsible for building data pipelines, feature engineering, doing ML POC, & productionizing models in scalable manner. It is combination role with data science & software engineering background. This role is unique role as full stack developer of data science. 


  • Ensure data science code is maintainable, scalable and debuggable
  • Automate and abstract away different repeatable routines that are present in most machine learning tasks
  • Bring the best software development practices to the data science team and helps them speed up their work
  • Choose best operational architecture together with devops team
  • Constantly look for performance improvement and decides which ML technologies will be used in production environment
  • Design and develop ML pipelines using heterogeneous sources, integration APIs, and provide Hadoop ecosystem services for data science applications/flows
  • Data modeling – Finding useful patterns (correlations, clusters, eigenvectors). Predicting properties of previously unseen instances (classification, regression, anomaly detection, etc.).
  • Partner with domain owners, data analyst and product owners, to better understand requirements, finding bottlenecks, resolutions, etc.
  • Build data ingestion from various source systems to Hadoop using Kafka, Spark Streaming etc.
  • Transform data using data mapping and data processing capabilities like MapReduce, Spark/Spark SQL with a good understanding on data science requirements
  • Supports Big Data and batch/real time analytical solutions leveraging transformational technologies like Apache Beam


  • Good understanding in linear algebra, machine learning and statistics
  • Working experience in prototyping machine learning use cases
  • Have good analytical sense to ensure data quality and validate features
  • 0 to 3 years of industrial experience with the Hadoop ecosystem and Big Data technologies
  • Good hands-on development experience with machine learning models
  • Hands-on experience with the Hadoop eco-system (HDFS, MapReduce, Hive, Impala, Spark, Kafka, Kudu, Solr)
  • Must be comfortable with reading and writing Scala/Pyspark, Python, Java code, Bash script.
  • System level understanding – Data structures, algorithms, computability and complexity, and computer architecture (including  distributed processing)
  • Understanding bias and variance, overfitting and underfitting, missing data, data leakage, etc.
  • Must be comfortable with reading and writing Scala/Pyspark, Python, Java code, Bash script.


  • MS. or Ph.D in Computer Science or relevant quantitative science


We are the global cybersecurity leader, known for always challenging the security status quo. Our mission is to protect our way of life in the digital age by preventing successful cyberattacks. This has given us the privilege of safely enabling tens of thousands of organizations and their customers. Our pioneering Security Operating Platform emboldens their digital transformation with continuous innovation that seizes the latest breakthroughs in security, automation, and analytics. By delivering a true platform and empowering a growing ecosystem of change-makers like us, we provide highly effective and innovative cybersecurity across clouds, networks, and mobile devices.

Our Security Operating Platform is built for automation. It is easy to operate, with capabilities that work together, so customers can prevent successful cyberattacks. They can use analytics to automate routine tasks, so they can focus on what matters. We are known for continuously delivering innovations; and with Application Framework, we extend that to an open ecosystem of developers that benefit from our customers’ existing investment in data, sensors, and enforcement points.

Learn more about Palo Alto Networks here and check out our fast facts