At ASI, the business problem is to ensure the quality, reliability, and real-world readiness of software and AI driven autonomous systems, specifically in the fields of agriculture, construction, landscaping, and logistics.
Requirements
- Strong understanding of AI behavior, model evaluation, data pipelines, and real time system interactions.
- Hands on experience with automated testing frameworks, simulation tools, scenario generation, or hardware in the loop validation.
- Ability to design testing architectures that scale across cloud, embedded, and robotics environments.
- Experience analyzing metrics, failure cases, regression patterns, and long tail performance challenges.
- Strong programming skills in languages used for verification and automation such as Python, C++, or similar.
- Experience with CI/CD systems, version control, and structured testing workflows.
- Strong problem solving and analytical capabilities with a focus on reliability and safety.
Responsibilities
- Define and own the AI driven testing strategy for autonomy across simulation, hardware, software, and real-world validation.
- Develop automated verification pipelines that use AI, data driven analysis, and intelligent test generation to evaluate system performance at scale.
- Design tests that expose edge cases, failure modes, rare events, and long tail conditions critical for safe autonomous operation.
- Integrate testing workflows with model training pipelines, deployment systems, data infrastructure, and robotics platforms.
- Build metrics, dashboards, and evaluation frameworks that measure reliability, robustness, safety, and regression impacts across model updates.
- Use simulation tools, digital twins, and scenario generation to replicate diverse operating conditions and evaluate autonomous behaviors.
- Validate AI performance on hardware in the loop, software in the loop, and real-world testing environments.
Other
- Bachelor's degree in Computer Science, Software Engineering, or a related field.
- 3-5 years of experience in software testing, validation engineering, machine learning engineering, or autonomous systems development.
- Ability to communicate testing results, risks, and recommendations clearly to technical and non-technical stakeholders.
- Ability to collaborate with research, robotics, infrastructure, and product teams to define and execute complex testing plans.
- Commitment to fostering a diverse, inclusive, and equitable workplace
