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About the Role
Invisible is building a reinforcement learning capability within its research organization, focusing on evaluation methodology, benchmarks, and RL environments for frontier labs and enterprise clients. As a Research Engineer, you will influence the methodology of model evaluations, translating research questions into production systems. This role is for individuals who want to design the approach and write the code to prove it out.
Responsibilities
- 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
Requirements
- Production-quality code written daily; this is a hard requirement
- Fluency in Python and comfort across the modern ML stack
- Real experience building evaluation systems, RL environments, or training and inference infrastructure
- Hands-on experience with modern agentic flows
- 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
Skills
- Python
- ML Stack
- Evaluation Systems
- RL Environments
- Training Infrastructure
- Inference Infrastructure
- Agentic Systems
- Reinforcement Learning
- Frontier Model Evaluation
Work Type
- Hybrid
Benefits
- Bonuses and equity are included in all full-time offers.
About the Company
- Invisible Technologies makes AI work. Our end-to-end AI platform structures messy data, automates digital workflows, deploys agentic solutions, measures outcomes, and integrates human expertise where it matters most.
- Our platform cleans, labels, and structures company data so it is ready for AI. It adapts models to each business and adds human expertise when needed, the same approach we have used to improve models for more than 80% of the world’s top AI companies, including Microsoft, AWS, and Cohere.
- Our successes span industries, from supply chain automation for Swiss Gear to AI-enabled naval simulations with SAIC, and validating NBA draft picks for the Charlotte Hornets.
- Profitable for more than half a decade, Invisible reached $134M in revenue and ranked as the number two fastest growing AI company on the 2024 Inc. 5000. In September 2025, we raised $100M in growth capital to accelerate our mission of making AI actually work in the enterprise and to advance our platform technology.
- 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.
Equal Opportunity
- We’re an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or veteran status, or any other basis protected by law.
- Due to a high volume of candidates, Invisible may use automated decision-maker technologies to filter candidates based on response to our application questions and other provided information. Our use of automated decision-making enables us to be efficient by providing a manageable list of possible candidates that meet our mandatory hiring criteria. If you object to our use of automated decision-making please contact us.