Role template

Research Scientist / ML Engineer resume template & writing guide (2026)

A resume for an industry research lab or applied-ML role blends academic rigor with product impact: it should cover publications, shipped projects, and your technical stack. Two pages are acceptable for senior or heavily published candidates.

5 matching templates for you

PRONEW
Impact

A top row of quantified wins (growth, scale, efficiency) leads with results; great for outcome-driven roles

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PRONEW
Impact Teal

Teal take on the impact layout: a top row of quantified wins, results first

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PRONEW
Impact Green

Green take on the impact layout: a top row of quantified wins

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PRONEW
Impact Ink

Charcoal take on the impact layout: a top row of quantified wins

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PRO
Scholar

Serif with a light sidebar and top color bar, scholarly feel; for consulting, research, and academia

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Selecting "Use this template" on any template creates a new resume with that theme preset; your existing resume is untouched.

AI resume tips

  • 1Group top-tier papers by area (CV, NLP, RL, systems) and note venue tier (CVPR, ICML, NeurIPS).
  • 2Quantify industry projects by impact: serving scale, QPS, model size, and gains over baseline.
  • 3Show open-source contributions: merged PRs to PyTorch, TensorFlow, or Hugging Face, and your GitHub.
  • 4List your stack: PyTorch, JAX, CUDA, Triton, Megatron, DeepSpeed, and TensorRT.
  • 5Highlight competition results (Kaggle, ImageNet, GLUE/SuperGLUE) with placement.
  • 6Emphasize end-to-end ownership: driving a model from training to production.
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