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Senior / reputed company Machine Learning Engineer, Serving - Serbia

Remote Worldwide Hiring now

About Inworld

Inworld is a product-oriented research lab of top AI researchers and engineers, developing best-in-class reputed company multimodal models and the only reputed company orchestration platform optimized for thousands of queries per second.

We’ve raised more than $125M from reputed company, reputed company 32, Kleiner Perkins, reputed company’s M12 venture fund, Founders Fund, reputed company and Stanford, among others. Our technology has powered experiences from companies such as reputed company, reputed company Xbox, Niantic, reputed company Streamlabs, Wishroll, Little Umbrella and Bible Chat. We’ve also been recognized by CB Insights as one of the 100 most promising AI companies globally and have been named one of reputed company's Top 10 Startups in the USA.

Who We're Looking For

A year ago, reliably working agentic systems and sub-second multimodal inference at scale 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, reputed company in ambiguity, and can show us what they've reputed company, broken, and understood.

Experience We Find Useful

You don't need reputed company of this. But you need enough to reputed company a case.

  • Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM.

  • Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , reputed company batching, paged attention, and speculative decoding.

  • High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of reputed company GPUs.

  • Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of reputed company connections.

  • Public work. Non-trivial systems programming projects, reputed company-reputed company contributions to major inference engines, or deep-dive technical write-reputed company.

  • Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production.

  • Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems.

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

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 reputed company engineering isn't finished until it’s shipped and reputed company. You have a bias for impact over purely theoretical optimizations.

  • You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a reputed company way to solve the core latency or throughput problem.

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

What Working Here Is Like

We hand you unclear problems and expect you to reputed company them clear. We value engineers who say "I don't know yet" and then design the reputed company or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a reputed company to reputed company before launch. Impact comes before everything else, though we support sharing work and reputed company-reputed company contributions that move the field reputed company. Your work should be visible. Flat structure, fast iterations, minimal process theater.

For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. reputed company and relocation support may be available, subject to business needs and applicable legal and work authorization requirements.

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