Staff AI Engineer/Scientist — Explainable, Trusted AI

Seekr; Austin (TX); Hybrid; USD 180,000 - 280,000; Full time

Benefits offered by this job

Equity ownership (RSUs)

Unlimited PTO

Flexible hybrid work environment

401(k) with company match

Health, dental, vision, and life보험

Job summary

Seekr is advancing reliable AI explainability and governance across cloud, on-prem, edge, and air-gapped environments. The role spans research and engineering, requiring deep ML expertise and production-grade coding, with emphasis on interpretable, auditable AI systems used in mission-critical contexts.

We value candidates who can translate state-of-the-art ideas into robust production capabilities, and who can collaborate with product and customer teams to integrate explainability into

Qualifications

• 8+ years of experience in AI engineering and/or AI research/science roles.
• Strong background in machine learning and modern AI systems, including LLM/VLMs, agent frameworks, RAG, or adjacent applied ML systems.
• Ability to move between research and engineering.
• Production-grade coding capability and prototyping skills inspired by state-of-the-art papers.
• Experience designing experiments and evaluating ambiguous technical tradeoffs.
• Fluency with AI coding assistants and modern developer workflows.
• Strong Python and software engineering fundamentals, with testing, code review, CI/CD, debugging, and performance analysis.
• Clear communication and collaboration across technical and non-technical partners.
• Reside near Austin, TX or Reston, VA and able to work 3 days per week in office.

Responsibilities

• Design explainability capabilities to help users understand why a model produced a given output and what influenced it.
• Design contestability capabilities to capture corrective feedback and improve systems over time.
• Work on related areas like hallucination detection, continual-learning agents, and translating ideas into prototypes and production features.
• Contribute across the AI system lifecycle including model development, inference, deployment, and monitoring.
• Collaborate with product, design, and customer teams to make explainability practical in real workflows.
• Use AI coding assistants effectively while maintaining strong judgment and code quality.

Skills

Python

ML systems

Research to engineering

Explainability

CI/CD

Experimentation

Communication

Team collaboration

Education

Master's or PhD in CS/ML/AI/Statistics

Tools

Kubernetes

Argo CD

vLLM/LLM frameworks

Git

Job description

Seekr is advancing reliable AI explainability and governance across cloud, on-prem, edge, and air-gapped environments. The role spans research and engineering, requiring deep ML expertise and production-grade coding, with emphasis on interpretable, auditable AI systems used in mission-critical contexts.

We value candidates who can translate state-of-the-art ideas into robust production capabilities, and who can collaborate with product and customer teams to integrate explainability into