Fortinet Principal Machine Learning Engineer 

United States, California, Sunnyvale 

982320156

Responsibilities

• Design and develop models that have high precision and low false positive rates.
• Augment model outputs to facilitate security personnel to better investigate and remediate flagged activities or vulnerabilities.
• Lead projects that directly influence our enterprise and consumer offerings with expectations of developing code that ships.
• Conduct thorough data investigations across a massive number of customer accounts and cloud sources to ensure data driven success.
• Improve efficiency, scalability, and stability of various system resources.
• Build roadmaps and goals in partnership with engineering and product teams.
• Work cross-functionally with other Engineering, Data Science, Product Management, Support, Sales teams as well as Customers to deliver quality platform capabilities.
• Review, design, mentor and code, and make sure what we ship adheres to high engineering standards
• Demonstrate good communication skills and present work to company leadership and at company-wide events

Minimum Qualifications

• Bachelor’s degree in Computer Science or related, relevant field
• 7+ yearsof relevant experience
• Have Delivered Production Machine Learning Models and Infrastructure
• Adhere and Mentor others on Development Lifecycles from Data Analysis, Training, Validation, to Deployments.
• Solid foundation in Computer science fundamentals and distributed systems.
• Experience in one or more data stores including SQL Databases, Snowflake, Postgres, Redshift, Hadoop, Cassandra, etc.
• Ability to build systems that balance scalability, availability, and latency.
• Great communication skills and a team player.

Preferred Qualifications

• M.S or Ph.D relevant to Machine Learning, Mathematics, or Statistics.
• Used at scale or contributed to the development of services in the Cloud (AWS, GCP, Azure)
• Experience in containerized deployment or Kubernetes.
• Experience in graph data algorithms and processing.
• Experience with one or more Machine Learning Frameworks such as torch, scikit-learn, pandas, tensorflow, huggingface, transformers.
• Experience with generative AI technologies such as AWS Bedrock, Retrieval Augmented Generation, Prompt Engineering, Natural Language Processing/Generation.
• Maintains practice in keeping up with Academia and Industry State of the Art or relevant research experience.

Wage ranges are based on various factors including the labor market, job type, and job level. Exact salary offers will be determined by factors such as the candidate's subject knowledge, skill level, qualifications, experience, and geographic location.