Staff Machine Learning Engineer, Ads ML Efficiency

Technologies named in the posting

How Rolefit scores this role

• Stack overlap (50%). Every technology named in the posting is compared with your selected stack, weighted by how rare it is across the whole index — a niche match counts for more than Docker.
• Seniority fit (16%). The level in the posting is compared with the level assessed from your years and depth.
• Title alignment (16%). Whether the role is actually pitched at your field rather than adjacent to it.
• Freshness and filters (18%). Newer postings, your work type and your target region all move the score.

The score you see on a shortlist is specific to you — the same posting scores differently for a different stack. Run the assessment once and this role either makes your top 30 or it does not.