AI Researcher — Distillation

Featherless AI; Poland; On-site; PLN 298,379 - 383,631; Full time

Benefits offered by this job

Real ownership over research direction

Strong support for publishing and open research

Access to meaningful compute and production-scale problems

Job summary

An innovative AI company in Poland is seeking an AI Researcher focused on model distillation to enhance the efficiency of models. This role involves designing novel distillation techniques, collaborating with engineers for implementation, and publishing high-quality research. The ideal candidate has a strong foundation in machine learning, experience with model distillation, and a track record of research publications. This position offers a chance for ownership in a Series A startup with a commitment to open research.

Qualifications

• Strong background in machine learning research.
• Hands-on experience with model distillation or related topics.
• Publication experience in research papers.

Responsibilities

• Design and evaluate model distillation techniques.
• Research tradeoffs between model size, latency, memory, and accuracy.
• Collaborate with engineers to productionize research outcomes.

Skills

Machine learning research

Model distillation

PyTorch

Communication skills

Education

PhD/Post-doc in a relevant field

Job description

About the Role

We’re looking for an AI Researcher focused on model distillation to help us push the frontier of efficient, high-performance models. You’ll work on turning large, expensive models into smaller, faster, and more deployable systems—while maintaining or improving quality.

This role is ideal for someone who enjoys publishing research, working close to real systems, and seeing their ideas move from papers → code → production.

What You’ll Work On

• Design and evaluate model distillation techniques (teacher–student training, self-distillation, layer-wise distillation, representation matching, etc.)
• Research tradeoffs between model size, latency, memory, and accuracy
• Develop novel distillation approaches for:
  • Large language models
  • Long-context or specialized architectures
  • Inference-constrained environments
• Run large-scale experiments and ablations; analyze results rigorously
• Collaborate with engineers to productionize research outcomes
• Write and submit research papers to top-tier venues (NeurIPS, ICML, ICLR, COLM, etc.)
• Contribute to internal research notes, technical blogs, and open-source projects when appropriate

What We’re Looking For

Required

• Strong background in machine learning research
• Hands‑on experience with model distillation or closely related topics (compression, pruning, quantization, representation learning)
• Publication experience (conference or journal papers, workshop papers, or arXiv preprints)
• Solid understanding of deep learning fundamentals (optimization, training dynamics, generalization)
• Fluency in PyTorch (or equivalent) and research-grade experimentation
• Ability to clearly communicate research ideas, results, and limitations

Nice to Have

• Experience distilling large language models
• Work on efficiency-focused research (latency, memory, throughput)
• Experience with long-context models or non-Transformer architectures
• Open-source contributions in ML or research tooling
• Prior startup or applied research experience

Why Join Us

• Real ownership over research direction at a Series A stage
• Strong support for publishing and open research
• Tight feedback loop between research and real-world deployment
• Access to meaningful compute and production-scale problems
• Small, highly technical team with deep ML and systems expertise

Example Backgrounds

• ML researchers from academia transitioning to industry
• Research engineers with published work in model efficiency
• PhD / Post‑doc graduates or industry researchers who still want to publish