Performance Test Engineer -AI/ML

Job Title

Experience:

Location:

About Us

We are building a foundational performance testing team focused on ensuring the stability and scalability of our innovative AI utilities and AI-created tools. We seek a skilled Performance Test Engineer with proven expertise in enterprise-level performance testing and a strong aptitude for complex systems.

Key Responsibilities

• Design and implement performance testing strategies for applications integrating Machine Learning (ML) models and AI components.
• Develop robust load scripts using tools like

  JMeter

  ,

  LoadRunner

  , or

  NeoLoad

  .
• Execute

  load modeling

  ,

  capacity planning

  ,

  stress

  ,

  endurance

  , and

  failover testing

  to uncover system bottlenecks.
• Monitor system resources (CPU, memory, network, storage, GPU) using APM tools such as

  Dynatrace

  ,

  New Relic

  , or

  Prometheus

  .
• Analyze test results and deliver actionable insights to engineering teams for performance optimization.
• Collaborate with

  Development

  ,

  MLOps

  , and

  DevOps

  teams to embed performance testing into CI/CD workflows.
• Validate performance impacts of model updates, data pipelines, and varying AI/ML workloads (e.g., inference latency, training throughput).
• Maintain and enhance performance testing frameworks and automation tools.
• Create and execute functional test cases based on user stories and requirements.
• Perform manual and semi-automated testing of GenAI features, validating model outputs, UI behavior, and end-to-end flows.
• Track and manage defects through resolution and support

  UAT

  and

  production readiness

  validation.

Required Qualifications

• 3-5 years of hands-on experience in

  Performance Testing & Engineering

  .
• Proficiency with at least one performance testing tool:

  JMeter

  ,

  LoadRunner

  , or

  NeoLoad

  .
• Strong understanding of

  system architecture

  ,

  cloud platforms

  (AWS, Azure, GCP),

  networking protocols

  , and

  database performance tuning

  .
• Scripting expertise in

  Python

  ,

  Java

  , or

  Groovy

  for test automation.
• Excellent analytical and communication skills to convey findings to technical and non-technical stakeholders.

Desired Qualifications (Nice to Have)

• Experience testing performance of

  AI/ML systems

  ,

  data pipelines

  , or

  microservices

  serving ML inferences.
• Familiarity with performance nuances of

  LLMs

  ,

  computer vision

  , or

  NLP

  workloads.
• Exposure to

  Docker

  ,

  Kubernetes

  , and

  service mesh

  performance testing.
• Knowledge of

  statistical analysis

  for interpreting performance metrics.