• We are hiring a very small number of exceptional engineers. • This role is for people who ship fast and ship well, and who have already proven they can do that when the stakes and the pace were highest. • Signals that you might be a great fit include owning a system that scaled from a few thousand to millions of users, shipping significant work in surprising windows, having side projects, or being an early or key engineer somewhere that grew fast.

Role Description Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. This opportunity involves: - Designing computational material science problems to challenge a frontier AI model. - Ensuring problems have verifiable answers by code and require specialized tools like ObsPy, instaseis, pyrocko, MITgcm, flopy/MODFLOW, or others. - Running each problem inside a sealed Linux container with the tool pre-installed and a programmatic judge that grades the model's answer. As an expert author, you: - Pick an anchor tool and design a problem that hinges on its waveform-processing kernels, geophysical inversion routines, sub-surface flow solvers, or community-validated data pipelines. - Write a Python reference solution, supply input files and model or domain definitions where needed. - Decide the numerical answer and how close the model needs to get — with a domain-appropriate tolerance — to count as right. - Test the problem against the model in batches of parallel attempts, tuning the problem difficulty until the agent only succeeds in a small number of attempts. - Submit the task to a senior reviewer in your subfield for feedback to ensure task quality is high. - Tune the problem against batches of parallel runs of the agent, aiming for a pass rate in the 10–30% band. - Learn how agents cut corners, where a simulation stalls, and how flow or inversion models converge. Qualifications - Degree in Material Science or related field. - 2+ years of research, applied, or teaching experience. - Python proficiency for writing reference solutions. - Fluency with — or strong willingness to independently learn — at least one scriptable package: ObsPy, instaseis, pyrocko, MITgcm, xmitgcm, flopy / MODFLOW, or GeoPandas. - Ability to design problems that genuinely require a specialized solver. - Strong written English (C1+). - No prior experience with the listed tools? You're still welcome to apply — as long as you're ready to get up to speed on your own and hit the ground running. Requirements - This opportunity is a good fit for material scientists & engineers with experience in Python, open to part-time, non-permanent projects. Benefits - Compensation of up to $35 per hour equivalent, depending on level and pace of contribution. - Compensation varies across projects depending on scope, complexity, and required expertise. - Note that other projects on the platform may offer different earning levels based on their requirements. Project Time Expectations - Tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. - This is an estimate, not a guaranteed workload, and applies only while the project is active.

Role Description This opportunity involves designing computational material science problems to challenge a frontier AI model. The problem must have an answer verifiable by code and require a specialized tool like ObsPy, instaseis, pyrocko, MITgcm, flopy/MODFLOW, or others. Generic data wrangling around synthesized toy data won't suffice. Each problem runs inside a sealed Linux container with the tool pre-installed and a programmatic judge that grades the model's answer. - Pick an anchor tool and design a problem that hinges on its waveform-processing kernels, geophysical inversion routines, sub-surface flow solvers, or community-validated data pipelines. - Write a Python reference solution, supply input files and model or domain definitions where needed. - Decide the numerical answer and how close the model needs to get — with a domain-appropriate tolerance — to count as right. - Test the problem against the model in batches of parallel attempts, tuning the problem difficulty until the agent only succeeds in a small number of attempts. - Once satisfied with the task, submit it for review to a senior reviewer in your subfield for feedback to ensure task quality is high. - Calibration requires patience, tuning the problem against batches of parallel runs of the agent, aiming for a pass rate in the 10–30% band. - Learn how agents cut corners, where a simulation stalls, and how flow or inversion models converge. Qualifications - Degree in Material Science or related field. - 2+ years of research, applied, or teaching experience. - Python proficiency for writing reference solutions. - Fluency with — or strong willingness to independently learn — at least one scriptable package: ObsPy, instaseis, pyrocko, MITgcm, xmitgcm, flopy / MODFLOW, or GeoPandas. - Ability to design problems that genuinely require a specialized solver. - Strong written English (C1+). Requirements - No prior experience with the listed tools? You're still welcome to apply — as long as you're ready to get up to speed on your own and hit the ground running. Benefits - For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. - Compensation can be up to $45 per hour equivalent, depending on level and pace of contribution. - Compensation varies across projects depending on scope, complexity, and required expertise.

• Develop overall product planning by contributing to/creating stories for complex features in areas of responsibility. • Organize, lead and finalize feature review sessions for complex business issues/requirements and document resulting decisions. • Create the functional design to address complex business processes or issues or to address requirements of product features. • Configure or develop within the Sitecore CMS; review and verify operation of new vendor release features. • Engage in pair-programming and Test-Driven Development full time to develop websites based on Sitecore CMS. • Provide training for other team members and users; assist in developing team bench strength.