Machine Learning Engineer.

Home Careers Machine Learning Engineer All careers We're hiring Sentinel Machine Learning Engineer. Help build the AI quality scoring layer Runflow runs in front of every image and video we ship. Hands-on ML, in production tomorrow, at scale. Remote global Full-time / contract Senior IC + equity Apply now How we hire sentinel evaluatelive auto-rotates hover/focus to pause 01 router Prompt “professional headshot, navy suit, neutral background” Decision use_case: headshot analyzers: 3 criteria: 3 02 analyzers Subjectrunning Layoutrunning Surfacerunning 03 criteria → score Identity preserved 96 Composition 92 Surface quality 88 sentinel score 94 pass ship The role Sentinel is the AI quality scoring layer Runflow runs in front of every image and video we ship. It decides what's good enough to deliver, what needs to be fixed, and what to throw away. It's how we keep output quality predictable at the volumes our customers run. We're hiring a Machine Learning Engineer to push that scoring layer forward and extend it across new content types. The work is hands-on ML applied to a real product. The model you train today is in production tomorrow, scoring real customer outputs. If you've trained, fine-tuned, and quantised small specialised models, built eval pipelines that someone actually relied on, and have strong opinions on when an LLM is the right tool vs. when a sub-100ms specialised model is, this is for you. Quick facts TeamSentinel Reports toHead of AI LocationRemote global TypeFull-time or contract CompensationSenior IC + equity StartASAP Representative projects What you'd ship in your first 6 months. Concrete, shippable, on the live roadmap. Not hypothetical. We expect every one of these to land. Project 01 Build the eval harness that catches regressions before they ship Labelled samples per use case (good + bad), CI integration, regression alerts on every prompt change or model swap. Make Sentinel itself testable. Project 02 Find Sentinel's blind spots, then add the analyzers that close them Audit where Sentinel passes outputs customers later flag, where it rejects outputs that were actually fine. Pick the highest-impact gap, design the new analyzer (researching the best embeddings model for human-identity comparisons, for example), train, quantise, ship into the pipeline. Project 03 Extend Sentinel from images to video, scoring temporal consistency on Seedance and Kling Define the criteria that matter for video (identity drift, motion artifacts, scene continuity, lip sync where it applies). Build the analyzers. Ship it. Sentinel scores video by quarter-end. Responsibilities What you'll be doing. You'll own the full lifecycle, from prototype to production at scale. Architect the evaluation pipeline, router, preprocessors, judges, for image and video Train, fine-tune, and quantise specialised neural networks (face, pose, segmentation, OCR, embeddings, depth) Design dynamic rubrics that adapt to use case, headshot vs. product vs. fashion vs. video Spawn LLM judges per criterion. Decide model, prompt, complexity tier Extend Sentinel from images to video, temporal consistency, motion, identity drift, lip sync Build the eval harness, labelled samples per use case, CI regression alerts Push the LLM router toward the cost / quality / latency frontier (Lite / Flash / Pro tiers) Co-design the auto-fix loop with workflow engineers, generate → evaluate → fix → re-evaluate Requirements About you. You may be a good fit if… You've trained or fine-tuned a small neural network end-to-end, datasets, loss curves, the works You've shipped quantised inference (INT4/INT8) and know what trade-offs are acceptable in production You've designed an evaluation pipeline for any generative task and made it run reliably You have strong opinions on when to use an LLM vs. a specialised model, and can defend them You're comfortable shipping in TypeScript even if Python is your home, the system spans both You read recent ML papers (LLM-as-judge, eval design, video gen) and can summarise them in 3 sentences Strong candidates also have… Have published an evaluation framework or LLM-as-judge benchmark Have worked on AI video generation or video evaluation specifically Have hands-on experience with Qwen3-VL, SAM 3.1, OpenPose, Gemini Embedding 2, ArcFace, or similar specialised CV / multimodal models Have built a model router or orchestrator for multi-model production systems Have shipped open-source ML infrastructure or contributed to one of the libraries above What we're not looking for A specific number of years. A specific degree. A specific stack. We hire on whether you can ship end-to-end and whether you have taste. Everything else is noise. Tech stack What we work with. Backend Node.jsPythonPostgreSQLRedis ML ComfyUIPyTorchdiffuserstransformersONNXTensorRT Models Qwen3-VLSAM 3.1OpenPoseGemini Embedding 2ArcFace LLMs Gemini 3.1Opus 4.7 ThinkingMuse SparkQwen 3.5Kimi k2.6 How we hire Five steps. Decision speed is part of the offer. We move fast because senior candidates with multiple offers reward the team that respects their time. Whole loop fits in two weeks. 01/5 Application submitted Form, ~5 min We read every word of every application. No silent rejections, ever. Triaged within 5 business days Apply now 02/5 Take-home challenge 2 hours max, your time A small, real Runflow problem. We score the prompts and decisions you made as much as the output itself. Reviewed within 3 business days 03/5 30 minutes with the CTO 30 min, live Quick conversation about your take-home, the team, and how you work day-to-day. Decision in 48 hours 04/5 Paid challenge, 2 days 2 days, we pay for your time A bigger problem we pay you to work through. We care about outcomes, not process. AI tools more than welcome. Decision in 48 hours 05/5 Closing interview 90 min, live Casual chat with the two founders. Decision in 24 hours Show, don't tell. We value proof over promises. When you apply, include examples. Things that stand out: A small model you trained, fine-tuned, or quantised, repo + the eval that proves it works An evaluation rubric you've designed for a real problem, with the failure modes you caught Any work on video generation, video eval, or temporal modelling A multi-model system or router you've built, when does each model fire, why Apply Ready to ship? Five minutes. We read every word. Yes / no / not-now within 5 business days, always. You're applying for Machine Learning Engineer Sentinel Name* Email* Location optional, city, country, time zone Links* At least one, LinkedIn, GitHub, portfolio, Loom, anything. Show us 1–3 things you've built that prove you can ship end-to-end.* Repos, posts, demos, anything. Specifics beat resume bullets. 1500 left What's a problem you solved with AI as the execution layer, not just chat?* We care that you reach for AI as a default tool, not occasionally. 1000 left Show us a product you find beautiful. Why?* Taste is non-negotiable. We want your real opinions. 800 left Which AI tools are in your daily workflow? Pick all you actively use, not just tried. How much is AI helping you these days? A sentence or two. Skeptical, force multiplier, in between, where it shines, where it doesn't. 600 left Share a Claude Code session that shipped a feature end-to-end. Optional but high-signal. We want to see how you actually work with AI, the prompts, the back-and-forth, the corrections. Whole session, snippet, Loom, gist, anything. 3000 left When have you most successfully hacked a non-computer system to your advantage? Optional. Bureaucracy, supply chain, a conference badge, social dynamics, anything. We collect signal here. 1000 left Most recent role + company Just the title + company name. We don't need a CV. 200 left When could you start? Salary expectation Confidential. A range is fine. 200 left Describe an evaluation pipeline you've built or a smaller model you've fine-tuned or quantised. What was the hardest part, and what would you do differently?* Specifics. Datasets, metrics, infra, the bug that took two weeks. 1800 left Anything else? Optional. A short note, a question, a relevant detail we missed. 500 left We commit to a yes / no / not-now within 5 business days. Always. No silent rejections. Other open roles Maybe one of these instead. We hire builders, not roles. If none fit exactly, the open application is at the bottom. 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