Demo

Test Engineer-AI/LLM

OPPO
Palo Alto, CA Full Time
POSTED ON 10/30/2025
AVAILABLE BEFORE 12/27/2025
OPPO US Research Center is seeking a meticulous and innovative AI/LLM Test Engineer to join our cutting-edge AI team. In this critical role, you will evaluate the performance, reliability, and safety of Large Language Models (LLMs) in real-world product scenarios and test end-to-end generative AI solutions. Your work will directly shape how users experience AI-powered features by ensuring robustness, accuracy, and alignment with product goals. This is a unique opportunity to pioneer testing methodologies for next-generation AI systems at the forefront of technology.

Requirements

Core Testing & Evaluation

  • Design and execute performance tests for LLMs across diverse product use cases (e.g., chatbots, content generation etc.)
  • Develop automated test frameworks to evaluate LLM outputs for accuracy, bias, safety, and coherence
  • Conduct end-to-end testing of integrated generative AI solutions, including APIs, data pipelines, and user interfaces

Optimization & Validation

  • Collaborate with ML engineers to validate fine-tuned models and optimize prompts for target scenarios
  • Analyze model failures, edge cases, and adversarial inputs to identify risks and improvement areas
  • Benchmark LLM performance against industry standards and product-specific KPIs

Collaboration & Quality Assurance

  • Partner with product, engineering, and research teams to define test requirements and acceptance criteria
  • Document defects, performance metrics, and test results to drive data-driven improvements
  • Advocate for AI ethics and safety through rigorous testing of fairness, bias mitigation, and content moderation

Innovation & Tooling

  • Build scalable tools for synthetic test data generation, prompt variation testing, and automated evaluation workflows
  • Stay current with advancements in generative AI testing, including red-teaming techniques and evaluation frameworks (e.g., HELM, Dynabench)
  • Propose novel testing strategies for emerging challenges (e.g., hallucinations, context drift)

Basic Qualifications:

  • Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field, or equivalent practical experience
  • 1 years of experience in software testing, data science, or ML validation, with exposure to AI/ML systems
  • Proficiency in Python and testing frameworks (e.g., PyTest, Selenium)
  • Hands-on experience evaluating LLMs in production environments (e.g., GPT, Claude, Llama, Gemini)
  • Strong analytical skills for dissecting model behavior, statistical performance, and failure modes
  • Familiarity with cloud platforms (GCP, Azure, or AWS) and MLOps tooling (e.g., MLflow, Weights & Biases)
  • Experience with version control (Git) and agile development methodologies

Preferred Qualifications:

  • Master's degree in AI, Machine Learning, or a related field
  • Expertise in prompt engineering, LLM fine-tuning (e.g., LoRA, RLHF), or optimization techniques
  • Experience with automated evaluation tools (e.g., LangChain, TruLens) or LLM-specific test suites
  • Knowledge of data pipelines, SQL/NoSQL databases, and API testing (e.g., Postman)
  • Background in statistics, quantitative analysis, or data visualization for test insights
  • Contributions to AI safety/ethics initiatives or open-source LLM evaluation projects
  • Experience testing mobile-integrated AI solutions (Android/iOS)

Benefits

OPPO is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

The US base salary range for this full-time position is $100,000-$200,000 bonus long term incentives benefits. Our salary ranges are determined by role, level, and location.

Salary : $100,000 - $200,000

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