Machine Learning Engineer.

Yes, if they are relevant to your target role. Publications demonstrate deep technical knowledge and original thinking. Place them in a dedicated section below experience. For industry roles, emphasize how published research translated into practical applications or influenced production system design.

List notable rankings (top 1%, gold medals) in a competitions or achievements section. Briefly describe the problem and your approach. Kaggle results are most impactful for early career candidates; senior engineers should lead with production ML systems but can include competitions as supplementary evidence.

Most Machine Learning Engineer resumes should be one page for candidates with under 10 years of experience and two pages for senior professionals. Prioritize relevance over length. Every line should earn its place by demonstrating value to the target role.

Update your Machine Learning Engineer resume every time you change roles, complete a major project, or earn a new certification. Even when not actively job searching, review it annual to add recent accomplishments. This ensures you are always prepared when an opportunity arises.

Use professional, readable fonts like Calibri, Arial, or Garamond at 10 to 12 point size for a Machine Learning Engineer resume. Stick to black text, clear section headers, and generous white space. Avoid decorative fonts, bright colors, and complex layouts that can cause ATS parsing errors.

For Machine Learning Engineer candidates with less than 10 years of experience, one page is ideal. Senior professionals with extensive relevant experience can use two pages. The key is that every line adds value. Padding a resume with irrelevant content hurts more than it helps.