Sr. Staff Machine Learning Engineer

Job summary

Santa Clara, California, United States Product Engineering Ref ID: JR-019576 Our Mission At Pal***®, we’re united by a shared mission—to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts.

Qualifications

• If you’re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you’re in the right place.
• If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us!
• Strong background on machine learning and ML frameworks (e.g., TensorFlow, PyTorch)
• Experience with Infrastructure-as-Code (IaC)
• Master's or PhD in Computer Science or a related technical field.
• Experience in the cybersecurity domain or with network security products.
• Expertise with containerization and orchestration
• experience, and work location.
• For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/com-missioned roles) is expected to be the annual range listed below.
• The offered compensation may also include restricted stock units and a bonus.
• 147,000.00 - $237,500.00/yr
• Our Commitment

Responsibilities

• As a Principal Software Engineer, you will provide technical leadership in designing and delivering robust, next-generation cloud security solutions.
• Provide technical leadership for end-to-end solution delivery, collaborating with cross-functional teams (Product, SRE, QA, and Support) to align engineering efforts with business objectives.
• Drive the development of scalable cloud security architecture through a balance of strategic planning and hands-on coding.
• Establish and evangelize best practices for model versioning, reproducibility, auditing, and compliance to ensure code quality and data privacy across the organization.
• Architect and lead the entire ML lifecycle, from initial development and training to production deployment and real-time inference.
• Build and maintain automated, resilient systems for continuous integration, delivery (CI/CD), and monitoring of backend and machine learning components.
• Continuously evaluate and integrate cutting-edge MLOps

Skills

Degrees

Industry

Company size

Security clearance