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MacPaw

AI Research Scientist

RemoteNot specified
Published
Role
Research
Salary not disclosed
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No BS summary

AI Research Scientist with deep experience in NLP or ML, strong LLM optimization knowledge, and Python programming skills. Must have a solid understanding of linear algebra, probability, and statistics. Upper-intermediate English or higher required for scientific writing and collaboration.

Core skills

LLM optimizationLLM efficiency

Required skills

Natural Language Processing (NLP)machine learningquantizationKV-cache compressionspeculative decodingdistillationparameter-efficient fine-tuningLoRAadaptersmixture-of-experts (MoE)PythonPyTorchJAXTensorFlowlinear algebraprobability theorymathematical statistics

Optional skills

performance engineeringcode profilinglow-level optimizationGPUMetalC++training localized LLM modelsrunning localized LLM models

Required languages

English Upper-intermediate

What you'll do

  • Prepare fundamental research proposals within our specialized LLM efficiency and optimization streams.
  • Investigate new directions in LLM optimization by surveying relevant academic publications, formulating hypotheses, and running deep-dive experiments.
  • Collaborate closely with internal research scientists and external academic labs on joint research projects and scientific publications.
  • Work alongside the applied research stream to surface, validate, and transition relevant research prototypes into downstream production environments.
  • Contribute to a strong publication record at top-tier international AI conferences.
  • Take full ownership of your research niche, driving initiatives from ideation to implementation with a high degree of independence and autonomy.
  • Take part in internal knowledge-sharing sessions and weekly paper clubs to consistently improve domain expertise.

What they require

  • Deep experience in Natural Language Processing (NLP) or a similar machine learning domain, gained through solid academic work, industry experience, or both.
  • Strong theoretical and practical understanding of recent LLM optimization techniques (ex. quantization, KV-cache compression, speculative decoding, and distillation).
  • Direct hands-on experience with parameter-efficient fine-tuning (including LoRA and other adapters) and mixture-of-experts (MoE) architectures.
  • Advanced prototyping skills and a proven ability to implement complex algorithms and architectures directly from academic papers.
  • Fluent programming capabilities in Python and modern frameworks such as PyTorch, JAX, or TensorFlow.
  • Robust fundamental knowledge of linear algebra, probability theory, and mathematical statistics.
  • Upper-intermediate level of English or higher for active scientific writing, international lab collaboration, and conference presentations.
  • A track record of publishing original research at international research conferences in AI/ML/SE/HCI domains.
  • Practical experience in performance engineering, including code profiling and low-level optimization (GPU, Metal, C++...).
  • Hands-on experience training, running, or deploying localized LLM models on device frameworks like MLX.

The company behind CleanMyMac, Setapp, ClearVPN, and a growing ecosystem of products used by millions of people worldwide.

SoftwareMid-size
Salary not disclosed