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Machine learning engineer resume template

An ML resume is a metrics report: AUC moved, latency cut, spend saved, scale served. This template's model-card styling frames exactly that — mono-accented contact spec, bracketed headings and grouped stack skills — while staying one parseable column that screening software reads clean.

Free forever · no watermark · switch to any of the 283 templates without retyping

Built for

  • ✓ML engineers owning models from training to serving
  • ✓Data scientists moving into production ML roles
  • ✓Backend engineers specialising into ML infrastructure

What you get

  • ✓Live on-page editing — click any text and type, paginated like the final PDF
  • ✓Selectable-text PDF export with clickable email and portfolio links
  • ✓AI import: upload your old resume PDF and land in this template, editable
  • ✓Scored 92/100 — interview-ready against the 30 published rules, measured by exporting this exact template. Certified: we only badge templates at 90 or above, a stricter bar than the 85 our checker calls interview-ready, so the design leaves headroom for your own content.
Cora Blakely
Machine Learning Engineer, Ranking and Recommendations
cora.blakely@example.com
(555) 402-1187
Austin, TX
corablakely.com/corablakely
Summary

Machine learning engineer with six years shipping ranking and recommendation systems to production. Owns the models behind 40% of an e-commerce company's revenue, lifted add-to-cart 11% with a two-tower retrieval model, and cut training cost by half with a feature store she designed. Measures the offline gain, then trusts only the A/B test.

Experience
Senior Machine Learning Engineer — Shoply, e-commerce marketplace
08/2022 – Present
  • Own the product recommendation stack serving 12 million users; recommendations drive 40% of marketplace revenue
  • Replaced the collaborative-filtering retriever with a two-tower model; add-to-cart up 11% and revenue per session up 6% in a 4-week A/B test
  • Designed the feature store (Feast on Redis and BigQuery) used by 9 models; training cost down 52% and feature skew incidents to zero
  • Built the real-time reranker (under 25 ms p99) with a distilled cross-encoder and a Triton serving path
  • Lead a pod of 4 engineers; run the model review and the weekly experiment readout with product
Machine Learning Engineer — Finlytica
06/2020 – 07/2022
  • Built the transaction categorisation model (96% accuracy on 1.2 million transactions a day) and its retraining pipeline
  • Shipped a fraud-risk ranking model that cut manual review volume 38% at the same catch rate
  • Introduced offline evaluation with holdout cohorts and drift monitoring; two silent regressions caught before release
  • Wrote the team's model-card and launch-checklist standard, adopted company-wide
Data Science Intern — Dell Technologies
05/2019 – 08/2019
  • Prototyped a demand-forecasting model for 400 SKUs that beat the planning baseline by 14% MAPE
Skills
Modelling
Ranking and retrieval (two-tower, cross-encoders)Recommender systemsGradient-boosted treesOffline and online evaluationA/B testing
Engineering
PythonPyTorchTensorFlowSparkSQLFeastTriton and TorchServe
Platform
GCP (Vertex AI, BigQuery)KubernetesAirflowMLflowTerraform
Education
M.S. Computer Science, Machine Learning — University of Texas at Austin2018 – 2020
B.S. Computer Science — Purdue University2014 – 2018
Talks and Writing
Speaker, RecSys 2025 industry track: two-tower retrieval at marketplace scale
Author of the internal series on feature stores, 6 posts read by 300 engineers

Frequently asked questions

Is CVLoom really free?

Yes — editing, all 283 templates, and PDF download are free, with no watermark and no card. There is no account at all: no signup, no login, nothing to cancel.

Will my PDF have selectable text for ATS systems?

Yes. Exports are generated by a real browser engine, so the PDF has true selectable text, embedded fonts, and clickable links — the things resume parsers need.

Can I switch templates without retyping anything?

Yes — your content and the design are stored separately, so switching templates re-flows the same content instantly and losslessly. Try every one of them.

What metrics belong on an ML engineer resume?

Model quality (AUC, precision/recall), serving performance (p99 latency, throughput), business impact (conversion, fraud caught) and cost (GPU spend, token bills). One metric per bullet — and name the stack that produced it.

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