QA Engineer (AI Systems)

Experience with human-in-the-loop evaluation workflows (labeling pipelines, inter-rater reliability, rubric design).

Background in ML/data science sufficient to read model evals and statistical significance.

Experience red-teaming or doing adversarial/security testing on ML systems.

Familiarity with observability/tracing tools for LLM applications (e.g., LangSmith, Arize, Langfuse, Weights & Biases).

Experience testing AI systems in industrial, IoT, or operational technology (OT) environments.

Prior experience setting up eval infrastructure from scratch at a startup or fast-moving team.

What We're Looking For A QA engineer who wants to define what quality means for autonomous, real-world AI systems.

Someone who can build rigorous evaluation infrastructure for problems that don't have a single right answer.

A systems thinker who enjoys turning ambiguous agent behavior into measurable, trustworthy signals.

A strong collaborator who partners well with ML engineers, backend engineers, and Forward Deployed teams.

Innovative Environment : Play a critical role in transforming heavy industries through groundbreaking AI and automation technologies.

Collaborative Culture : Be part of a team that values innovation, discipline, and continuous improvement.

Professional Growth : Benefit from significant opportunities for career development and advancement.

Competitive Compensation : Enjoy a comprehensive salary and equity package reflective of your expertise and contributions.

If you're passionate about AI quality and eager to help define what trustworthy autonomous systems look like in heavy industry, we'd love to connect.