AI research engineer with 4 years of experience turning research ideas into reliable experiments on efficient language model training. Co-authored 3 workshop and conference papers and built the training codebase used by a 12-person research group. Brings fast prototyping, reproducible experimentation and strong systems skills for large GPU runs.
Experience
AI Research Engineer, Northfield AI Institute (Cambridge, MA)
Sep 2022 – Present
Built a JAX training framework for 125M to 7B parameter models used by 12 researchers across 4 projects
Implemented sparse mixture-of-experts layers that matched dense baseline quality with 35% fewer training FLOPs
Co-authored 3 papers on data selection and efficient attention, including one accepted at ICLR
Cut failed long runs from 1 in 4 to 1 in 20 with checkpoint validation and loss-spike alerts
Research Engineer Intern, Nimbus Search (Mountain View, CA)
Jun 2021 – Sep 2021
Reproduced 3 dense retrieval papers and benchmarked them on internal query logs
Built an ablation harness that reduced experiment setup from days to hours
Education
M.Eng. Electrical Engineering and Computer Science, Massachusetts Institute of Technology (Sep 2021 – Jun 2022)
B.S. Computer Science and Engineering, Massachusetts Institute of Technology (Sep 2017 – Jun 2021)
Skills
Research: Language model pretraining, mixture of experts, data selection, ablation design
A strong AI Research Engineer resume shows the systems you built, the scale they run at, and the measurable effect on speed, reliability or cost. Put your most relevant recent role first and make every bullet show a result, not a duty.
Sections, in order
Summary
Experience
Projects
Skills
Education
Length: One page for most candidates; move to two only if every line is relevant.
Summary: Write two or three lines: your role, your strongest skills, and one result that proves them.
Skills to feature
Programming languages
System design
Cloud platforms (AWS, GCP, Azure)
CI/CD
Testing and code review
Databases and SQL
Observability
Security fundamentals
APIs and integrations
Technical documentation
Example bullet points
Rebuilt the checkout service in Go, cutting p95 latency from 900 ms to 180 ms for 2M monthly users
Introduced contract tests and staged rollouts, reducing production incidents by 45% in two quarters
Migrated 30 services to Kubernetes with Terraform, lowering cloud spend by $250k a year
Tips from recruiters
Group skills by category (for example "Languages: Go, TypeScript") so recruiters and ATS parsers find them quickly.
Link to a repository, demo or write-up for at least one project you can talk about in depth.
Name the stack inside each bullet; keyword matching happens at the bullet level, not only in the skills list.
Recommended templates
Classic (ATS-friendly): Jake's-style LaTeX classic: small caps and hairline rules
Tech (ATS-friendly): Developer style: mono headings and tags, sans body
Modern (ATS-friendly): Clean single column with accent headings and rules
AI Research Engineer resume FAQ
What should a AI Research Engineer resume include?
A AI Research Engineer resume should show the systems you built, the scale they run at, and the measurable effect on speed, reliability or cost. Use these sections in this order: Summary, Experience, Projects, Skills and Education. Put your most relevant recent role first and make every bullet show a result, not a duty.
What is the best resume template for a AI Research Engineer?
Classic, Tech and Modern work well for AI Research Engineer roles. They are single-column with standard headings, so applicant tracking systems (ATS) parse them reliably.
How long should a AI Research Engineer resume be?
One page for most candidates; move to two only if every line is relevant.
Which skills should a AI Research Engineer put on a resume?
Prioritize the skills named in the job posting. Common ones for AI Research Engineer roles are Programming languages, System design, Cloud platforms (AWS, GCP, Azure), CI/CD, Testing and code review and Databases and SQL.
How do I write strong AI Research Engineer resume bullet points?
Start with an action verb, say what you did, and end with a measurable result such as latency, uptime and deploy frequency. For example: "Rebuilt the checkout service in Go, cutting p95 latency from 900 ms to 180 ms for 2M monthly users."