Get AI-powered advice on this job and more exclusive features. This range is provided by Cisco. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range $177,600.00/yr - $225,900.00/yr Meet the Team The mission AI Defense at Cisco is to provide end-to-end protection for Enterprise AI applications. The team has deep expertise in AI and security and is an active contributor to cutting-edge research and standards on AI and security. At Cisco, our mission is to build AI Security at Cisco scale as well as lead the next generation of AI infrastructure for disruptive security products across Cisco. We are pioneers in all aspects of AI security from supply chain to development time model vulnerability detection to protecting against real-time attacks on deployed AI applications. Your Impact Join Cisco's AI Defense ML Team and be at the forefront of AI Security innovation. Here, you will tackle ever-evolving challenges and leverage the dynamic AI landscape to craft solutions that ensure AI safety and security for all. As a Data Scientist, you'll have the chance to design the data platform driving cutting-edge ML algorithms that detect and protect against AI security risks. You'll gain deep expertise in the fields of both AI and security, engaging with all facets of detection techniques and their deployment in production environments. You will collaborate with a talented team of ML engineers and security experts and play a pivotal role in developing groundbreaking AI solutions. Shape the future of AI safety and Security with us and make an enduring impact on AI adoption across the world! As a Data Scientist, you will: Analyze customer telemetry logs to identify patterns of failure, convert them into actionable insights for the ML team to improve the ML models. Build high-quality evaluation datasets, conduct FP/FN analysis on existing ML models using these datasets, and help devise model improvement strategies. Conduct analysis of training dataset quality, identify low-quality data clusters, and build de-duplication algorithms to continually improve ML performance by improving training data quality. Collaborate with Research to develop data generation algorithms for complex ML challenges, including variation-robustness and multi-lingual data generation. Explore data generation strategies for textual and multi-modal data for Robust Intelligence use cases. Work with Threat Intelligence to inform new data generation techniques by analyzing adversarial methods and customer telemetry. Design scalable pipelines for large semi-structured data using advanced distributed cloud data warehouse technologies. Contribute to our overall machine learning and data management culture as a member of the team. Minimum Qualifications A BS with minimum 3 years or MS in Computer Science/Engineering. Experience with some backend datastore similar to Snowflake or Databricks. Background in Statistical data analysis and/or Math. Strong programming skills in generic programming languages such as Python or Golang. SQL proficiency for complex data transformations and querying, strong understanding of semi-structured data handling. Preferred Qualifications An attitude of hands-on learning and constant experimentation to decompose and understand problem areas. Comfortable with fast iterative style development in an environment that requires autonomous thinking, risk-taking, and bias for action. Familiarity with modern data warehousing technologies like Snowflake/Databricks and data formats like Snowpark/Iceberg. Ability to use the latest GenAI technologies and creative prompting. Comfortable with traditional ML frameworks like PyTorch, TensorFlow, FastAI, etc. Excellent written and verbal communication skills, strong analytical and problem-solving skills.
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