Tech Marketing & Performance Engineer

Tech Marketing & Performance Engineer  Power the systems that power the world's most demanding work.
The Tech Marketing and Performance Engineer plays a foundational role in HP's Workstation business. You'll support HP's high-performance portfolio by executing structured testing and contributing to performance validation efforts. This team works at the intersection of hardware, software, and performance, collaborating with internal engineers and industry partners to help ensure HP workstations deliver reliable and measurable results.
In this role, you will build core technical skills by applying computer science fundamentals and learning Linux-based workflows to execute standardized performance benchmarks, support basic automation, and create clear technical documentation. You'll work on well-defined tasks under guidance from senior engineers, gaining exposure to advanced platforms, emerging AI workflows, and professional computing technologies.

Key Responsibilities  ISV Software & Platform Support   Support validation and testing of professional software applications (ISVs) across HP workstation platforms.
Assist with ISV certification testing, executing test plans and documenting results.
Quickly learn and navigate complex software applications to support benchmarks, demos, and workflows.
Help reproduce issues and gather data for escalation and resolution.
Performance Testing & Analysis   Execute standardized benchmark tests aligned to defined customer workflows.
Support execution and validation of AI and data science workloads, including emerging use cases (LLMs, inference, etc.).
Collect and organize performance data to ensure accuracy and repeatability.
Support identification of performance anomalies and assist in investigation efforts.
Linux Development, Automation & Tooling   Work in Linux environments using command-line tools to manage systems and execute tests.
Contribute to automation tools and scripts for benchmarking, data collection, and test execution.
Support development efforts related to:
Benchmark automation frameworks
AI workflow testing pipelines
System setup and environment configuration
Assist with Linux-based development and potential environment/container setup.
Technical Documentation & Enablement   Create and maintain technical documentation including test procedures, configurations, and performance summaries.
Support development of technical demos, workflow walkthroughs, and enablement materials.
Help translate performance data into simple, understandable insights for broader audiences.
Collaboration & Professional Development   Work with performance engineers, systems engineers, and technical marketing staff.
Actively seek opportunities to learn and contribute, demonstrating self-motivation and ownership of assigned tasks.
Build technical understanding of:
Workstation hardware platforms
GPU/CPU performance
ISV workflows and AI use cases
Impact & Scope   Contributes through execution of performance tests, automation support, and technical deliverables.
Works on well-defined problems with guidance, while building technical independence.
Gains exposure to AI workflows, professional applications, and real-world systems performance challenges.
Knowledge & Skills  Required   Strong foundation in computer science fundamentals.
Python proficiency (hands-on experience beyond coursework strongly preferred)
Experience or familiarity with Linux environments and command-line tools
Ability to learn quickly and adapt to complex technical applications and workflows
Preferred   

Experience with AI- data science frameworks (e.g. PyTorch, Tensor Flow, Transformers)
Exposure to Docker containers or container-based development environments

Experience with scripting or automation (Python, Bash, etc.)
Familiarity with data science tools or environments
Exposure to benchmarking, performance testing, or system-level analysis
Education & Experience   Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or related field, or equivalent experience.
Typically 0-2 years of relevant experience through internships, or academic projects, or entry-level roles.
Exposure to Linux, operating systems, or…