Research Engineer / Scientist – Optimization
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 Engineer/Scientist (Optimization) at Percepta, you’ll work at the intersection of AI research and real-world impact. You will advance the frontier of decision-making for critical industries by combining modern machine learning with rigorous optimization research. You’ll collaborate closely with our Embedded Product Managers (EPMs) and engineers to ensure our most sophisticated decision systems are both innovative and pragmatically useful in transforming how companies operate.
Responsibilities
Set and drive ambitious research programs that expand what’s achievable in data-driven decision-making.
Invent new optimization-and-ML methods for high-impact problems such as planning, scheduling, routing, pricing, and inventory.
Build high-fidelity simulators and rigorous benchmarks that mirror real-world constraints, uncertainty, and multi-objective trade-offs.
Bridge research into practice by partnering with our engineers to rapidly prototype solutions and implement successful research ideas.
You may be a good fit if you
Hold a degree in Computer Science, Operations Research, Industrial Engineering, or Applied Mathematics (MS/PhD preferred) or have equivalent research/ industry experience.
Have depth in operations or mathematical optimization (LP/MIP/MINLP, CP, stochastic/robust optimization, causal inference).
Have experience in novel machine learning techniques for Operations Research.
Are comfortable implementing and debugging large-scale optimization systems.
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 that excites you, let's chat, even if you don't meet all of the qualifications above.