# Closure — Founding AI/ML Engineer Type: Full-time | On-site | San Francisco, CA · New York City, NY Compensation: $125,000–$200,000 + 0.3%–1% equity Hiring count: 2 Visa sponsorship: None available (U.S. work authorization required; FBI/CJIS clearance sponsored) Reports to: Co-Founder ## About Closure Closure helps law enforcement search evidence and solve crime. Police and prosecutors across the U.S. use Closure to accelerate investigations into homicides, cold cases, and other major offenses by reducing digital evidence overload. The team includes ex-Palantir and ex-IDF engineers who've built national-scale systems before. Backed by Y Combinator, CRV, Hawktail, Liquid2, and Adverb, with live deployments and paying agency customers. Founded: 2025 | Team size: 1–10 (Seed) | Total funding: Not stated on role page (outreach template cites €7M+ — uncorroborated, treat with caution) Industry: Public safety / law-enforcement AI Website: closure-intel.com Office: San Francisco, CA · New York City, NY ## Why Candidates Should Join - Mission with real weight: Bring technical excellence to public safety — accelerate homicide, cold-case, and major-crime investigations for U.S. police and prosecutors. - Founding-level ownership: Early engineer shaping Closure's AI backbone end-to-end, from data flow design to production deployment; meaningful founding equity stake. - Serious backing and traction: YC-backed alongside CRV, Hawktail, Liquid2, and Adverb, with live deployments and paying agency customers already in production. ## Intake Call Summary - No intake call summary or transcript is present on the role page. Pull intake notes from Contrario separately if available. ## The Role An early engineer role building Closure's AI backbone — processing massive video, audio, and text datasets to surface investigative leads across backend infrastructure and applied ML. ### What You'll Be Doing - Build retrieval pipelines over large-scale video, audio, and text evidence datasets - Integrate LLMs/VLMs and deploy secure, distributed systems in sensitive environments - Ship end-to-end, from data flow design through production deployment - Surface investigative signals and leads from unstructured data - Work closely with founders on system architecture and technical direction Tech stack: Python, FastAPI, LangChain, PyTorch; LLM/VLM inference; distributed backend infrastructure ## Requirements - 4–6+ years of engineering experience, ideally 2+ in applied ML - Strong Python backend + ML ops familiarity (FastAPI, LangChain, PyTorch, etc.) - U.S. work authorization and willingness to undergo FBI background check - Deep technical communication skills (can explain systems and trade-offs clearly) - Production experience deploying LLMs/VLMs or custom ML inference pipelines - Experience understanding and scaling backend infrastructure (does not have to be an expert but must have solid knowledge) ## Green Flags - Built secure, distributed backend systems (Python/Go/TypeScript) - Demonstrated curiosity across both infrastructure and model-level work - Worked on real-time or high-throughput data systems - Prior early-stage or mission-driven startup experience - SWE and data engineering experience/knowledge ## Red Flags - Only academic or research exposure to AI (no production deployment) - Preference for large-company processes or siloed work - Weak understanding of data security / compliance requirements ## Role Details Salary$125,000–$200,000Equity0.3%–1%On-site policy In-person, NYC or SF, at least 3x/week Visa sponsorship None available; FBI/CJIS clearance sponsored Employment type Full-time Location San Francisco, CA · New York City, NY ## Screening Questions 1. Do you have valid U.S. work authorization and are you willing to undergo an FBI background check / CJIS clearance process? 2. Are you able to work in-person from NYC or SF at least 3x/week? 3. Are you ok with 25% travel on the job? 4. Do you have experience with RAG, speech-to-text, computer vision? 5. Why are you interested in this role and joining Closure? 6. Do you see yourself closer to the Research or Applied side of ML systems? 7. Do you see yourself as proficient in general backend engineering? 8. Do you have strong English communication skills? This is a requirement due to our customer base. ## Interview Process Stage 1 — Pending Approval — Candidates awaiting initial approval. Stage 2 — Intro Call w/ Co-Founder — Introductory call with a founder. Stage 3 — Leetcode — Coding assessment. Stage 4 — Systems — Designing a system under specific constraints. Stage 5 — Final Behavioral — Final behavioral round. Stage 6 — Offer Extended — Offer has been extended. Stage 7 — Hired — Candidate accepts and starts. ## Ideal Companies & Backgrounds Ideal Companies — Palantir, Anduril, Deepgram, Meta, Waymo, Arena, Palo Alto Networks, Pinterest, Ebay, Amazon