Research Engineer

About The Role

Invisible is building a reinforcement learning capability inside its research organization, focused on evaluation methodology, benchmarks, and RL environments for frontier labs and enterprise clients. As a Research Engineer, you'll work on how frontier models are measured, meaning the evaluations that labs and enterprises actually make decisions on, with direct influence over the methodology and not just its implementation.

You'll take a research question (how do we measure whether a model can do this work, and how do we make that measurement reproducible?) and turn it into a scoring framework, an evaluation architecture, or an environment design, then ship the production system that runs it. This role doesn't hand specifications to someone else to build, and it doesn't only build what others have specified. It's a fit for someone who wants to design the approach and write the code that proves it out.

Depending on level, the role reports to the Lead Research Engineer or, at Principal, directly to the VP of Research.

What You'll Do

• Design benchmarks and RL environments that measure real model capability for frontier labs and enterprise clients
• Originate evaluation methodology and translate it into scoring frameworks, rubrics, and evaluation architectures
• Write and ship the production code that implements your designs
• Build and maintain the data pipelines that feed evaluation runs
• Run the analysis that establishes whether a result holds, and make evaluations reproducible
• Partner with Research Scientists on methodology review, with Solutions Architects on client requirements, and with ML software engineers who build and maintain the underlying platform

What We Need

• Production-quality code written daily; this is a hard requirement
• Python & ML Stack: Fluency in Python and comfort across the modern ML stack
• Evaluation & Infrastructure: Real experience building evaluation systems, RL environments, or training and inference infrastructure
• Agentic Systems: Hands-on experience with modern agentic flows
• RL & Frontier Evaluation: Familiarity with reinforcement learning methods and how frontier models are evaluated; we weigh this more heavily than years of experience
• A track record of turning ambiguous research questions into working systems, and publishing or shipping the result

Additional information

You can find more information about our geographic pay tiers here. During the interview process, your Invisible Talent Acquisition Partner will confirm which tier applies to your location. For candidates outside the U.S., compensation is adjusted to reflect local market conditions and cost of living.

*Bonuses and equity are included in all full-time offers. Final compensation is determined by a combination of factors, including location, job-related experience, skills, knowledge, internal pay equity, and overall market conditions. Because of this, every offer is unique. Additional details on total compensation and benefits will be discussed during the hiring process.

What It's Like to Work at Invisible

At Invisible, we're not just redefining work-we're reinventing it. We operate at the intersection of advanced AI and human ingenuity, pushing the boundaries of what's possible to unlock productivity and scale. Ownership is at the core of everything we do. Here, you won't just execute tasks-you'll build, innovate, and shape the future alongside world-class clients pushing the boundaries of AI.

We expect bold ideas, relentless drive, and the ability to turn ambiguity into opportunity. The pace is fast, the challenges are big, and the growth is unmatched. We're not for everyone, and we're okay with that. If you're looking for predictable routines, this isn't the place for you. But if you're driven to create, thrive in dynamic environments, and want a front-row seat to the AI revolution, you'll fit right in.

Country Hiring Guidelines

Invisible is a hybrid organization with offices and team members located around the world. While some roles may offer remote flexibility, most positions involve in-office collaboration and are tied to specific locations. Any location-based requirements or hybrid expectations will be communicated by our Talent Acquisition team during the recruiting process.

AI Interviewing Guidelines

Our hiring team thoughtfully uses AI to support an efficient, engaging, and inclusive interview process. Since AI can also be a helpful tool for candidates, we've outlined expectations for using it ethically throughout your interview journey. Click here to learn more about how we use AI and our guidelines for candidates.