D'Eriq H.

Software Engineer

San Francisco, California, United States14 yrs 8 mos experience

Highly StableAI Enabled

Key Highlights

Expert in machine learning and AI-driven solutions.
Strong background in networking and infrastructure development.
Proven leadership in open-source engineering projects.

Stackforce AI infers this person is a Software Engineer specializing in AI, Networking, and Infrastructure within the tech industry.

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Skills

Core Skills

Machine LearningAiInfrastructureSoftware DevelopmentNetworkingDevopsReliability Engineering

Other Skills

AI-driven applicationsData pipelinesModel optimizationDistributed systemsLarge scale storage systemsNetwork software developmentNetworking devicesNetwork monitoringTooling developmentAutomationEngineeringBack-End Web DevelopmentFront-end Development

About

D'Eriq is an Engineer at Google working with the Internetworking team with a focus on tooling and compositional machine learning. They are also the engineering lead for several open-source projects. I have a strong background in developing and implementing complex networking solutions, and I am passionate about delivering high-quality software products. I am currently seeking executive positions in the software engineering field, where I can leverage my technical expertise to drive innovation and growth.

Experience

14 yrs 8 mos

Total Experience

4 yrs 5 mos

Average Tenure

1 yr 2 mos

Current Experience

Openai

Principal Software Engineer, Integrity

Feb 2025 – Present · 1 yr 2 mos

Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact.
Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives.
Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches.
Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices.
Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large.

Machine LearningAI-driven applicationsData pipelinesModel optimizationAI

Google

Software Engineer, Infrastructure

Feb 2017 – Feb 2025 · 8 yrs · San Francisco Bay Area

Build our platforms, systems and infrastructure using your strong background in distributed systems and large scale storage systems.
Manage individual projects priorities, deadlines and deliverables with your technical expertise.
Design, develop, test, deploy, maintain, and enhance software solutions.

Distributed systemsLarge scale storage systemsSoftware developmentInfrastructureSoftware Development

Facebook

Software Engineer, Network

Sep 2014 – Feb 2017 · 2 yrs 5 mos · Menlo Park, CA

Develop software to scale the Facebook production network
Work with networking devices and protocols
Integrate with other systems, evaluate third party solutions
Collaborate with Network Engineering team to automate various processes, build software infrastructure for network monitoring and analysis, aid in capacity planning and architecture change analysis.

Network software developmentNetworking devicesNetwork monitoringNetworkingSoftware Development

Netflix

DevOps Specialist

Jan 2011 – Jan 2014 · 3 yrs

Develop effective tooling, dashboards, alerts, and response to identify and address reliability risks.
Build tools and automation to reduce operational tasks, improve automatic issue identification and routing, and predict platform performance in accordance to SLAs based on overall platform health and progress.
Participate in on-call rotation to manage incident and to handle unknown/new issues.
Drive issue resolution and root cause identification with the various data infrastructure teams.
Evangelize best practices around collaboration and reliability to all encoding teams.

Tooling developmentAutomationReliability engineeringDevOpsReliability Engineering