How to source and screen Machine Learning Engineer candidates

Title variants to search

Postings and resumes rarely use one consistent title. Cover all of these when searching boards and your own database.

• Machine Learning Engineer
• ML Engineer
• AI Engineer
• MLOps Engineer

Starter Boolean search string

Paste this into a job board or resume database, then tighten it with location, work authorization and years of experience.

("Machine Learning Engineer" OR "ML Engineer" OR "AI Engineer" OR "MLOps Engineer") AND ("Python" AND "PyTorch or TensorFlow" AND "Model deployment and serving")

Google resume X-ray string

Replace City and ST with your target location. The intitle operators and exclusions steer Google toward resumes instead of job ads and templates. Check the privacy rules that apply before collecting contact details.

(intitle:resume OR intitle:cv) ("Machine Learning Engineer" OR "ML Engineer" OR "AI Engineer" OR "MLOps Engineer") ("Python" OR "PyTorch or TensorFlow" OR "Model deployment and serving") ("City" OR "ST") -job -jobs -sample -template -hiring

LinkedIn Recruiter variant

LinkedIn supports AND, OR and NOT in uppercase. Excluding junior and non-candidate titles keeps the list clean.

("Machine Learning Engineer" OR "ML Engineer" OR "AI Engineer" OR "MLOps Engineer") AND ("Python" OR "PyTorch or TensorFlow" OR "Model deployment and serving") AND NOT (intern OR trainee OR recruiter)

Must-have skills

If a candidate cannot speak to these, they are rarely a fit.

• Python
• PyTorch or TensorFlow
• Model deployment and serving
• SQL
• Cloud (AWS, GCP or Azure)

Nice-to-have skills

Use these to rank candidates who already meet the must-haves.

• MLOps (MLflow, Kubeflow)
• LLMs and RAG
• Docker
• Feature stores

Screening questions

Three questions that separate hands-on experience from keyword matching.

• Which model did you take to production and how do you monitor it?
• How do you detect and handle drift?
• Describe your experience with LLM applications.

Before you run these strings

Operator behavior differs by platform, so test each string on a small result set first. Keep every OR group inside parentheses, avoid piling on exclusions that can remove good candidates, and add location and work authorization last. The Boolean search cheat sheet and the Dice Boolean search guide cover the details.

Where automation helps

A machine learning engineer requirement is only valuable if you see it early and submit a resume that mirrors it. MatchWire scrapes job boards every 30 minutes, sweeps employer career sites on a regular schedule, matches each new posting to the consultants on your bench, and drafts an AI-tailored resume for matches you queue, so your recruiters spend time on the call, not the search.

Frequently asked questions