Machine Learning Engineer

Fortinet is looking for a Machine Learning Engineer to assist FortiCNAPP Team! Be a valuable member of the team that owns and operates high-availability, cross-cloud, large-volume, AI/ML infrastructure ecosystems. As a Machine Learning Engineer, you will help explore, refine, and build new techniques to improve the quality of ML models to capture anomalous and vulnerable cloud posture and activity as well as improve efficacy in security intrusion detection.

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.
• Work on 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.
• Analyze and 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 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   
• 3+ years of relevant experience 
• Knowledge and experience with Production Machine Learning 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. 

The US base salary range for this full-time position is $140,000-$215,000. Fortinet offers employees a variety of benefits, including medical, dental, vision, life and disability insurance, 401(k), 11 paid holidays, vacation time, and sick time as well as a comprehensive leave program.

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.

All roles are eligible to participate in the Fortinet equity program, Bonus eligibility is reviewed at time of hire and annually at the Company’s discretion.

Why Join Us:
We encourage candidates from all backgrounds and identities to apply. We offer a supportive work environment and a competitive Total Rewards package to support you with your overall health and financial well-being. Embark on a challenging, enjoyable, and rewarding career journey with Fortinet. Join us in bringing solutions that make a meaningful and lasting impact to our 660,000+ customers around the globe.

Fortinet is looking for a Machine Learning Engineer to assist FortiCNAPP Team! Be a valuable member of the team that owns and operates high-availability, cross-cloud, large-volume, AI/ML infrastructure ecosystems. As a Machine Learning Engineer, you will help explore, refine, and build new techniques to improve the quality of ML models to capture anomalous and vulnerable cloud posture and activity as well as improve efficacy in security intrusion detection.