Senior Applied Researcher
Posted 20 days ago · 0 applicants
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The role in plain words
- Strong applied research background (NLP/ML) with real production experience
- Fluency in context engineering, agent design and orchestration, and evaluation of LLM-based systems
- Execution and operations mindset, biased to ship
- Track record of building standards or tooling that lifts a team
- Comfortable owning ambiguous problems end to end with minimal oversight
- Experience on another applied-research or agent team
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Who this suits
Full job description
Original listing · kept for referenceAbout the Role
At Second Nature AI, we're building a cutting-edge, AI-powered conversation platform that lives in the browser, real-time audio, WebSockets, and everything that comes with it. We're looking for a Senior Applied Researcher and Team Lead to help shape how our conversational agents are designed, evaluated, and shipped reliably at production scale.
Key Responsibilities
• Partner directly with the Applied Research Team Lead to define and evolve team process, technical standards, and the quality bar for agent behavior.
• Take real user experience and data through the full arc, from concept to a reliable agent design to a shipped, production-grade product.
• Own or share ownership of the standing function of assessing AI tools, models, and providers for reliability and fit.
• Raise the technical bar across a team spanning research-leaning grad students to engineers newer to AI, and turn personal expertise into shared tooling and standards the whole team can use.
• Operate pragmatically inside current infrastructure constraints while flagging where structural fixes are needed.
Qualifications
• Strong applied research background (NLP/ML) with real production experience, shipped systems, not only research output.
• Fluency in the modern stack: context engineering, agent design and orchestration, and evaluation of LLM-based systems.
• An execution and operations mindset, biased to ship, comfortable defining good enough versus chasing optimal.
• A track record of building standards or tooling that lifts a whole team, or clear readiness to grow into that.
• Comfortable owning ambiguous problems end to end with minimal oversight.
Bonus Points
• Experience on another applied-research or agent team, bringing outside benchmarks and practices in.
Questions about this role
- This listing did not state a salary. We only show pay when the employer publishes it.
- Strong applied research background (NLP/ML) with real production experience, Fluency in context engineering, agent design and orchestration, and evaluation of LLM-based systems, Execution and operations mindset, biased to ship, Track record of building standards or tooling that lifts a team, Comfortable owning ambiguous problems end to end with minimal oversight