Search HeadStart's tech job index: query describes only the role ('backend engineer at a climate startup'); years, pay, place, company, employment type and dates go in their own fields, never in query. query ranks jobs by similarity but never narrows them: the total counts every job the filters allow, and less similar rows follow the close ones. To require a word (a language, 'ML', a title word), use keyword: each word must start a word, and a quoted phrase keeps its words together. In descriptions it can match only jobs with a stored description, and the answer says how many have one. For visa sponsorship or relocation use work_authorization, never keyword: a description that mentions sponsorship usually refuses it. Omit query to list the newest jobs that match the filters; similar_to a job id ranks by that job instead. With a query, sort orders only its closest matches (similarity 0.67+) — for a global order (the highest salary or newest anywhere) omit query and narrow with keyword and the filters. company matches as the site's company box does (any company name containing the text); beside category it needs a directory company: a key such as 'greenhouse:stripe', or an exact name. When company matched as text, tell the user so, since it also takes in any other employer whose name contains that text. sort salary orders by the low end of each stated range; without a currency it is ordered in USD. Jobs HeadStart's classifier is confident are not tech (a cashier, a process engineer) are left out unless include_non_tech is true; the answer says how many. Postings over max_age_days old (365 unless sent) are left out; totals count every other job the index serves, so they run higher than read_trends', which counts only jobs its classifier places in a tech category. Returns the total, one page of jobs with their ids, links and ages, and — when nothing matches — the filter costing the most.