Top Linux Jobs in San Diego, CA

The Technical Engineer leads app development and integration, collaborates with stakeholders, and ensures scalable solutions while managing data pipelines and quality assurance processes.

Provide Tier-3 DevOps support for customer deployments, install and configure Microsoft-based infrastructure, monitor and tune systems, run security scans, create and run PowerShell scripts, document environments, troubleshoot applications and networks, and collaborate with project teams to maintain production and test systems.

Build and improve a browser extension and serverless backend using a strongly-typed functional stack. Design algorithms to locate page elements, extract structured data, and integrate AI for web automation. Collaborate on a small distributed team focused on usability and reliability.

The Wastewater Specialist operates and maintains a wastewater pretreatment facility, ensuring compliance, performing laboratory analyses, and improving facility operations. Responsibilities also include regulatory reporting, inventory management, and equipment maintenance.

Build and ship performance-critical, low-latency software that interfaces with robot hardware. Own end-to-end data and inference pipelines, optimize latency and determinism, and work across kernel/firmware to autonomy stack with real robots.

Placement for a Quality Engineer to work at a customer site. Specific responsibilities, requirements, and scope will be provided by the recruiter and vary by customer.

The role involves performing vulnerability assessments, developing mitigation solutions, and preparing design solutions for natural hazards, while communicating findings to clients.

As a Machine Learning Engineer, you'll design and implement distributed systems for training large-scale ML models while optimizing performance under challenging conditions.

Architect and build scalable full-stack systems using TypeScript and multiple databases (SQL, MongoDB, Redis). Design server-side logic, APIs, and responsive front ends, deploy to cloud using containerization, mentor engineers, collaborate with product and design, and drive technical direction for an AI-powered sales product.

Lead modernization of operational data store, implementing data transfer methodologies, leveraging AI for migration and reconciliation, and collaborating across teams.