Time since we first saw it
Day 90
Up longer than most. Similar jobs usually come down between day 4 and day 77.
From 51 similar postings that came down. Coming down is not always a hire.
Senior Applied ML Engineer, Evals & Data
Reads like an AI Engineer role: building products on existing AI models.
Bengaluru · Bengaluru, Karnataka, India
Open 3 months, first seen by us 90 days ago- Pay
- Pay not listed
- Work setting
On-site — work setting source
Location type: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Tech — team source
Department: Tech
From the employer’s posting
Education & alternatives
- You can turn "the agent feels dumb" into a number, then move it. - Strong in TypeScript or Python. No PhD needed. - Bonus: multimodal AI, video, or fine-tuning.
Tools in this posting
- Python
- TypeScript
Source — Tool mentions in context
- You can turn "the agent feels dumb" into a number, then move it. - Strong in TypeScript or Python. No PhD needed. - Bonus: multimodal AI, video, or fine-tuning.
Posting record
Report an errorOpen 3 monthsWe first saw this posting 90 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Aug 15, 202690 days ago
- Recorded sightings
- 53
- Last seen by us
- Nov 13, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Cardboard is hiring
1 open job
- No new data jobs since August
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Demand for AI Engineer roles
New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
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About the role
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Job description
About
We're building the future of storytelling and video editing.
We're a small team that moves fast and builds things we're proud of.
We care obsessively about taste: in design, in product, in every detail.
We're solving these hard problems.
We're backed by a Tier-1 global fund, YC, and founders of billion dollar companies.
AI Engineering
Cardboard is a video editor you can talk to. Our agent makes real edits on the timeline. When it gets one right, it feels like magic. When it gets one wrong, it costs someone their afternoon.
We're hiring a Senior Applied ML Engineer to own how good the agent is: turn real failures into evals, evals into a bar the team trusts, and that bar into shipped improvements. This isn't research-only, prompt-only, or QA.
What you'll own
What "good" means for our agent, and datasets built from real usage.
Offline and online evals: automated checks, model graders, and human review.
Regression gates, and quality tracked alongside latency and cost.
Which models the agent runs on.
Who you are
You've shipped an LLM or agent system that real customers used.
You've built evals, datasets, or AI quality systems before.
You can turn "the agent feels dumb" into a number, then move it.
Strong in TypeScript or Python. No PhD needed.
Bonus: multimodal AI, video, or fine-tuning.
How we work
You own outcomes, not tickets: decide what to build, ship it, and check it worked.
You talk to users and look at the data.
You build with AI agents every day, and you're the taste and judgment in the loop.
What success looks like
Within your first six months:
The team trusts a quality baseline for our main agent workflows.
Production failures regularly become eval cases.
We can show measurable improvements in key editing workflows.
What you get
You'd be surrounded by people who are absurdly good at what they do. One started coding at 11 and shipped an app with 6M+ downloads in high school. One got into CS engineering at 14 and has been working on distributed systems for 8+ years. One's an ex-founder who took a company to 1.2M users and $300M+ in transactions. That's the team. We're looking for someone who'll raise the bar on how we measure and improve AI quality. Apart from that you'd get:
Competitive salary and founding-team equity.
Unlimited tokens across every AI model. Use whatever you want, as much as you want.
A healthy budget for AI tools and any peripherals you need to do your best work.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Bengaluru, Karnataka, India
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
AI answers unavailable
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