About Perle
At Perle.ai, we’re reimagining how training data is built. We believe the future of AI won’t be shaped by generic datasets, but by expert-driven annotation pipelines, cutting-edge workflows, and fearless builders who move fast and experiment relentlessly.
This isn’t just another job. This is a startup journey: fast, messy, and high-stakes, where your work directly defines how the most advanced AI models in the world are trained. We’re looking for an Ops Engineer who’s scrappy, resilient, and thrives in ambiguity. Someone who loves building systems quickly, isn’t afraid to break things, and is hungry for ownership.
If you want a safe 9 to 5 job, this isn’t it. If you want sweat plus grit plus equity that leads to legacy, keep reading.
The Opportunity
You’ll be part of the Product Operations team, the heartbeat of Perle.ai. This isn’t just ops, it’s the team that builds the first working prototypes of every tool and workflow for annotation projects. You’ll be the builder who takes ideas, customer requirements, and messy real-world constraints, and turns them into functioning systems that prove what’s possible.
Once validated, these prototypes will be delivered to our Engineering, Product, and Design (EPD) team to scale, refine, and harden into long-term solutions. You’ll work side by side with EPD and be in direct alignment with Product Ops Managers, ensuring every prototype ties back to real customer needs and product strategy.
The Ops Engineer team is core to Product Ops and will directly shape the product roadmap, annotation features, and operational capabilities of the company.
What you’ll do
- Set up, configure, and launch data annotation projects across text, audio, video, image, and specialized domains such as medical and legal. From guidelines to task structures, you’ll be the one making them real.
- Build prototypes of tools, workflows, and annotation systems, including UI/UX design and full-stack web applications that validate customer needs and internal hypotheses before they’re scaled by EPD.
- Build scrappy web-based dashboards, internal tools, and annotation interfaces that are functional and usable on day one.
- Work closely with Product Ops Managers to translate customer requirements into working prototypes.
- Partner directly with the EPD team to transition prototypes into production-ready systems.
- Write scripts, connect APIs, and automate pipelines to accelerate how we launch and scale projects.
- Be the first line of defense when pipelines break or projects stall. Troubleshoot live, fix things fast, and keep projects moving under pressure.
- Prototype, test, ship, and iterate constantly. Nothing will stay static; you’ll adapt workflows to evolving customer and team needs.
- Ensure that every dataset we deliver is structured, clean, and QA’d to customer expectations, even if it means getting hands-on with annotation yourself.
- Balance short-term hacks with long-term scalability, moving from “get it working today” to “make it run at 100x tomorrow.”
Who you are
- A scrappy engineer who’s just as comfortable writing quick Python scripts as building functional web tools with clean UI/UX.
- You thrive in ambiguity and fast-moving environments, figuring things out as you go without waiting for perfect processes.
- You’ve worked with annotation projects, training data, or ML workflows before and know what good data looks like.
- You understand the nuances of labeling across text, speech, and vision, and how to set projects up for success.
- You can design and implement full-stack solutions, from database logic to user-facing dashboards and annotation interfaces.
- You take personal responsibility for outcomes and feel proud of delivering results that move the company forward.
- You’d rather launch something imperfect today and improve it tomorrow than wait weeks for perfection.
- You know startup life isn’t 9 to 5 and embrace it because you see the upside.
Qualifications
- 3+ years of hands-on engineering experience, ideally in annotation projects, ML ops, or startup environments.
- Proficiency in Python, SQL, and scripting, with the ability to build, automate, and troubleshoot quickly.
- Strong full-stack development skills (React, Node.js, Django, Flask, or similar).
- Ability to design and implement UI/UX for internal and external web tools.
- Experience with data annotation tools, QA frameworks, and pipelines.
- Comfort working across cloud infrastructure such as AWS, GCP, or Azure, and connecting APIs.
- Strong debugging, problem-solving, and “fix it now” mentality.
- Bonus: exposure to medical or legal datasets, compliance workflows, or sensitive data annotation.
Why now?
We’re in the earliest days of Perle.ai. The foundation we lay now, from pipelines to annotation systems to early product prototypes, will define our trajectory. As an Ops Engineer on the Product Operations team, you won’t just run processes. You’ll invent them, scale them, and influence the product roadmap for the entire company.
This is your chance to be part of something rare: a startup where your fingerprints will be all over the product, the operations, and the future of AI.
If you want a seat at the table where the future of AI is being built, apply now.
