Research Scientist - World Modeling

Percepta

• $120K — $145K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • MS/PhD in Computer Science, ML, or related field, or equivalent experience
  • Deep understanding of LLM and ML fundamentals
  • Proficient in implementing and debugging large-scale ML systems
  • Motivated by impact in critical industries
  • Proven track record of execution
  • Excellent communication skills for both technical and non-technical audiences
  • Strong sense of ownership and passion for AI

Responsibilities

  • Identify impactful research problems and design strategies
  • Prototype and scale training pipelines for LLMs
  • Experiment with model architectures and optimization techniques
  • Contribute to high-performance distributed training infrastructure
  • Conduct large-scale evaluations with significant economic impact
  • Collaborate with applied AI engineers to integrate research into product features
  • Communicate research findings effectively to diverse stakeholders

Benefits

  • Collaboration with industry-leading partners
  • Opportunity to work on cutting-edge AI technology
  • Chance to impact critical industries like healthcare and finance
  • Open culture encouraging innovation and extreme ownership
  • Engagement with a motivated and rapidly growing team
Full Job Description
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.

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