Why This Role Stands Out
This role offers a unique opportunity to push the boundaries of large-scale language model development and deployment, directly impacting critical industries with cutting-edge AI. You'll thrive here if you're a skilled researcher or engineer eager to innovate in pre-training, fine-tuning, and specialized AI architectures. Apply now to join a growing team transforming institutions with applied AI.
Quick Overview
Job Description
Who We Are
Percepta’s mission is to transform critical institutions with applied AI. We care that industries that power the world (e.g. healthcare, manufacturing, energy) benefit from frontier technology.
To make that happen, we embed with industry-leading customers to drive AI transformation. We bring together:
Forward-deployed expertise in engineering, product, and research
Mosaic, our in-house toolkit for rapidly deploying agentic workflows
Strategic partnerships with Anthropic, McKinsey, AWS, companies within the General Catalyst portfolio, and more
Our team is a quickly growing group of Applied AI Engineers, Embedded Product Managers and Researchers motivated by diffusing the promise of AI into improvements we can feel in our day to day lives.
Percepta is a direct partnership with General Catalyst, a global transformation and investment company.
About the role
As a Research Scientist - World Modeling at Percepta, you'll build the systems that let us understand an operation at its full complexity. Real operations rarely arrive as clean, structured data: the ground truth about the operation lives scattered across claims, clinical notes, call transcripts, contracts, and the tacit judgment of operators. You'll build models and agents that learn to compress this mess into a tractable, continuously-updated representation — effectively a digital twin of the operation — that forecasters, user models, and optimizers downstream can all reason and plan against.
Responsibilities
Design and build learned world models that compress messy, multi-modal operational data (notes, transcripts, contracts, telemetry) into tractable, decision-relevant representations.
Model the transition dynamics of real operations — how a workforce, facility, or network evolves state-to-state — so downstream systems can run counterfactuals before a decision touches a real person or asset.
Build and validate digital twins of customer operations, benchmarked against replayable, real-world testbeds with defensible ground truth.
Partner closely with the forecasting and optimization teams to ensure your representations are the right substrate for calibrated predictions and for finding optimal actions.
Bridge research into practice by partnering with engineers to deploy world models into live customer environments and push toward end-to-end production systems.
You may be a good fit if you:
PhD degree in Computer Science, Operations Research, Industrial Engineering, or Applied Mathematics or have equivalent research/industry experience.
Have depth in simulation or world modeling
Have experience in novel machine learning techniques for control and optimization, including test-time search and reinforcement learning for sequential decision-making.
Are comfortable implementing and debugging large-scale optimization systems, and designing benchmarks with real, defensible ground truth.
Are motivated by impact in critical industries including healthcare, supply chains, energy, and finance.
Have a proven track record of execution.
Are an excellent communicator with both technical and non-technical stakeholders.
Enjoy extreme ownership.
Are passionate about AI's transformative potential
We’re working against an incredibly ambitious mission. It won’t be easy, but it will likely be the most fulfilling work of your career. If this excites you, let's chat, even if you don't meet all of the qualifications above.
Our Values
Dream bigger: We have the unique privilege of taking on the most ambitious problems and we should chase them with optimism, responsibility, and genuine belief that we can make it happen. We have to embrace the hard things when no one else will.
Heart in the game: What we're doing matters and we have to give a shit. Internally, that means fixing badness when you find it. Externally, it means honoring the trust our customers place in us with their most important problems. This isn’t a 9-5, nor is it a job we’re ever going to monitor your hours. We promise to put work in front of you that matters and in return, we ask you to promise to care.
Win for the customer: Everyone is an engineer and the job of an engineer is to deliver outcomes, not outputs. Everything we do—the products we build, the partnerships we launch, the strategy we set—exists to make our customers successful. Delivery is the strategy.
Make the call: Organizations are only as strong as the pace at which they make decisions. Everyone at Percepta should feel empowered to commit and shape the ambiguity in front of them. But "make the call" cuts both ways: make the decision and make the phone call. High-agency decision-making only works with high-bandwidth communication and we commit to never operate in silos.
Intensity with kindness: We believe in excellence in execution, candor in feedback, ruthlessness in prioritization, and survivalist urgency. We also believe you don't need to be an asshole to deliver on any of this. The trust built through shared kindness and vulnerability is what makes the intensity sustainable.
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