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Staff / Principal Research Scientist, Models - Switzerland

Join Inworld AI as a Staff/Principal Research Scientist to innovate in real-time voice models within a fully remote team in Switzerland.

Location
Switzerland
Compensation
Not disclosed
Level
staff
Type
full time · Remote

Posted by employer 10 months ago

First seen on Joblaze 2 months ago

Last verified on the company career page 23 hours ago

Requirements

Education
PhD

Not disclosed in this posting: compensation, years of experience, visa sponsorship.

Joblaze summary

Inworld AI seeks a Staff or Principal Research Scientist to tackle complex problems in real-time voice model development, focusing on both research and practical applications. Candidates should have a strong foundation in machine learning and natural language processing, with experience in areas like model training, evaluation, and multimodal systems. This role is ideal for individuals who thrive in ambiguous environments and prioritize impactful research over traditional academic outputs. The company fosters a collaborative atmosphere where innovative thinking and experimentation are highly valued.

Joblaze insights

  • Listed about 2 months ago — first seen on Joblaze September 3, 2026. Last confirmed on Inworld AI's careers page November 14, 2026.

Quick facts

Is the Staff / Principal Research Scientist, Models - Switzerland role remote?
Yes — Inworld AI lists this as a fully remote position.
What's the tech stack?
Joblaze extracted these technologies from the posting: AI/ML, Machine Learning, Multimodal Models, Natural Language Processing, evaluation, reinforcement learning.
What seniority level is this role?
Inworld AI targets staff-level candidates for this position.
Is this full-time or contract?
Full-time for this Staff / Principal Research Scientist, Models - Switzerland role at Inworld AI.

From the original posting

Who We're Looking For

A year ago, reliably working agentic systems barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood.

  • Foundation models: training, new architectures, RL, reward modeling, scaling

  • Evaluation: benchmarks, eval loops, quality measurement, LLM-as-judge, failure analysis

  • Frontier topics: multimodal models, agents, tool use, test-time compute, world models

  • Published research at ICML, ICLR, NeurIPS, EMNLP, ACL, or AAAI

  • PhD in ML/NLP — or equivalent practical experience you can point to

  • Public work: non-trivial AI side projects, interdisciplinary experiments, open-source contributions

  • Full-stack research ownership: you frame the question, run the experiments, write the paper, ship the result

  • Professional fluency in English (written and spoken) is required, as you will be collaborating daily with our US-based leadership and engineering teams.

If you learned through building, competitions, or collaborations outside academia, that counts. We care about evidence, not credentials.

Who Thrives Here

  • You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go

  • You believe research isn't finished until it’s shipped. You have a bias for impact over purely academic output

  • You don't just ship code; you obsess over the why. You’re the first to question an approach if you think there’s a better way to solve the core problem

  • You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make

What Working Here Is Like

We hand you unclear problems and expect you to make them clear. We value researchers who say "I don't know yet" and then design the experiment that finds out. We treat evaluation as a first-class research product, not a box to check before launch. Impact comes before publications though we support sharing work that moves the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater.

Location & Employment

  • Location: remote within Switzerland

  • Employment type: Full-time, permanent employment

  • Hiring model: Employment via Employer of Record (EOR)

Candidates must already have the legal right to work in Switzerland, as visa sponsorship is not available for this role. For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements.

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