Explainable AI Engineer — Trusted Production ML

Seekr; Austin (TX); Hybrid; USD 170,000 - 260,000; Full time

Benefits offered by this job

Equity ownership – RSUs

Unlimited PTO + 14 holidays

Flexible hybrid work – Austin & Reston

Job summary

Seekr is hiring for a senior AI engineer/researcher to advance explainable and trustworthy AI across production systems. You will bridge research and engineering to build, test, and deploy capabilities that reveal decision processes and data influence in mission-critical AI deployments.

The role involves collaborating with product and customer teams, improving robustness, monitoring, and performance while maintaining high standards for interpretable AI in complex environments.

Qualifications

• 5+ years in AI engineering or AI research/science roles.
• Strong background in ML and modern AI systems (LLMs/agents/RAG).
• Ability to move between research and engineering.
• Production-grade coding when needed; prototyping from papers.

Responsibilities

• Design explainability capabilities to show why models produced outputs and what influenced results.
• Capture corrective feedback and turn contested outputs into data improvements.
• Address hallucination detection and continual-learning from signals.
• Translate literature ideas into prototypes and production features.
• Contribute across model development, inference, deployment, and monitoring.
• Collaborate with product, design, and customer teams to integrate AI into real workflows.
• Utilize AI coding assistants within a robust engineering workflow with strong code quality.

Skills

Python

AI engineering

Machine learning

LLM/VLMs

CI/CD

Testing

Debugging

Team collaboration

Communication

Education

Master’s or PhD in CS/ML/AI

Tools

vLLM

SGLang

Kubernetes

Argo CD

Vector databases

Job description

Seekr is hiring for a senior AI engineer/researcher to advance explainable and trustworthy AI across production systems. You will bridge research and engineering to build, test, and deploy capabilities that reveal decision processes and data influence in mission-critical AI deployments.

The role involves collaborating with product and customer teams, improving robustness, monitoring, and performance while maintaining high standards for interpretable AI in complex environments.