Applied AI Researcher

Applied AI Researcher

Airis Labs transforms user generated content into actionable field intelligence for government agencies worldwide.

Our platform empowers frontline analysts with multi modal AI tools that extract clarity from chaos enabling rapid insight across fragmented, unstructured media.

Airis was founded by experienced startup operators and is backed by world class investors.

We are looking for an Applied Researcher, specializing in NLP / Speech / Audio / Computer Vision, to join our TLV based team.

What you'll do

• Build and deploy production-grade AI systems around LLMs, VLMs, speech, audio, NLP, and computer vision
• Design End to End pipelines- from problem framing and prototyping to evaluation, deployment, and iteration
• Work closely with product and engineering to turn complex customer needs into scalable AI solutions
• Improve system quality through prompt engineering, evaluations, structured outputs, and model optimization
• Own real world AI challenges with meaningful impact

Who are you?

• 3+ years of hands-on experience building and shipping AI/ML systems to production
• Strong experience working with modern foundation models (LLMs / VLMs)
• Fluent with modern AI tooling- frontier models, prompt design, structured outputs and hands-on experience using Claude Code / Cursor / similar AI agents as an integral part of the development workflow
• Strong engineering background with the ability to write clean, maintainable, production quality code that others can easily read, extend, and trust
• Experience with cloud and/or on-prem GPU deployments
• Strong product intuition and systems thinking
• Ownership mentality and ability to operate independently
• M.Sc. in CS, EE, Math, Physics, or related field

Bonus points for

• Video understanding experience
• Retrieval/search systems knowledge (vector DBs, embeddings, reranking)
• Experience evaluating VLMs and designing benchmarks
• Startup background
• Familiarity with intelligence or video analytics domains

Why Airis Labs?

• Small team of exceptional people
• Fast execution and real ownership
• Production systems already used by paying customers
• Meaningful problems with real world impact
• High ownership, healthy work life balance, no hero culture