Senior Scientist, Efficient LLM Inference & Optimization

United States Digital Space LLC; Zürich; Vor Ort; CHF 180.000 - 250.000; Vollzeit

Benefits dieser Stelle

Competitive compensation

Career growth and learning

Flexibility and ownership

Collaborative culture

Impactful AI projects

Zusammenfassung

Token Factory is seeking a Senior Applied Scientist to turn frontier inference bottlenecks into production-ready solutions. You will design experiments, write code, and collaborate with engineers to ship results as production components.

You will lead research programs on efficient LLM/VLM inference, publish credible work, and mentor teams while building prototypes and open artifacts for external credibility.

Qualifikationen

• PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied math, or a closely related field.
• Strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, serving systems, or related areas.
• Strong hands-on coding ability in Python and PyTorch; ability to move from idea to experiment to prototype quickly.
• Deep understanding of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving tradeoffs.
• Strong experimental design skills, including ablations, baselines, metrics, statistical reasoning, and failure analysis.
• Excellent written and verbal communication.

Aufgaben

• Own focused research projects from hypothesis through experiment, ablation, prototype, and production handoff.
• Prepare internal reports, technical blogs, or papers when the work is externally credible.
• Partner directly with MLEs to ensure research prototypes become usable production components.
• Define and execute research programs in efficient LLM and VLM inference with measurable production impact.
• Invent, evaluate, and productionize methods for quantization, QAT, distillation, speculative decoding, KV-cache reuse, and model/runtime co-optimization.
• Build high-quality prototypes in PyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks, then productionize them.
• Design rigorous evaluation methodology covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token.
• Publish papers, technical reports, blog posts, and open-source artifacts that build external credibility for the company Token Factory.
• Collaborate with MLE, GPU kernel, backend infrastructure, product, and customer teams to choose high-leverage research bets.
• Mentor engineers and scientists on experimental design, scientific rigor, and model/system tradeoffs.

Kenntnisse

Python

PyTorch

Experiment design

Research publications

ML systems

Ausbildung

PhD in CS/ML/related field

Tools

CUDA

Triton

Jobbeschreibung

Token Factory is seeking a Senior Applied Scientist to turn frontier inference bottlenecks into production-ready solutions. You will design experiments, write code, and collaborate with engineers to ship results as production components.

You will lead research programs on efficient LLM/VLM inference, publish credible work, and mentor teams while building prototypes and open artifacts for external credibility.