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. What this opportunity involves: - You design computational physics problems to challenge a frontier AI model. - The problem must have an answer verifiable by code and require a specialized tool like FEniCS, OpenFOAM, Meep, REBOUND, CAMB, or others. - Each problem runs 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 physics models, integrators, Monte Carlo kernels, or PDE discretisations. - Write a Python reference solution, supply input files and domain or initial condition 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 you're happy with the task, and it scores within range, the task goes to a senior reviewer in your subfield for feedback to ensure task quality is high. Calibration requires patience. You're tuning the problem against batches of parallel runs of the agent, aiming for a pass rate in the 10–30% band. Reaching that means: - Rewriting field configurations. - Tightening initial conditions and solver parameters. - Watching how the agents act. This time compounds in two directions. You come out of each task with deeper command of the anchor tool itself, and also get a hands-on working intuition for how a frontier model navigates complex electromagnetic, fluid, gravitational, and cosmological problems. Qualifications - Degree in Physics (Theoretical, Experimental, or Computational) 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 physics package: FEniCS / DOLFINx, OpenFOAM, Meep, MPB, openEMS, Geant4, PYTHIA8, ROOT / PyROOT, WarpX, REBOUND, MESA, CAMB, CLASS, or bilby. - Ability to design problems that genuinely require a specialized simulation tool. - 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 physicians with experience in Python open to part-time, non-permanent projects. Benefits - For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. - Contributors can earn up to $35 per hour equivalent, depending on their level and pace of contribution. - Compensation varies across projects depending on scope, complexity, and required expertise. - Please note that other projects on the platform may offer different earning levels based on their requirements.

• Lead end-to-end delivery of Data & AI programs across planning, execution, and governance • Build relationships with executives and key stakeholders to align on outcomes • Translate technical solutions into business value and strategy • Drive program governance including scope, risks, and dependencies • Oversee Microsoft Fabric implementations and data platform modernization • Coordinate cross-functional teams (engineering, analytics, AI) • Facilitate executive steering committees and decision forums • Develop adoption and change management strategies • Monitor delivery performance using KPIs, dashboards, and reporting • Support business development and client engagement activities

• Manage the entire sales life cycle from start to finish, including prospecting, identifying needs, presenting, and defining solutions. • Establish plans, structure deals, and manage relationships with prospects and customers within North American territories. • Effectively prospect, identify and drive a large number of sales opportunities through a complex enterprise sales cycle. • Drive business growth by cultivating a network of executive level contacts and utilizing pre-call planning and post-call analysis. • Represent EvolutionIQ at conferences, educational forums, and other industry events. • Collaborate with product management to refine product direction and communicate progress to leadership.

• Own and execute the technical SEO roadmap across Resident's brand portfolio. • Embed SEO best practices into new templates, components, site migrations, product launches, and experiments before they go live. • Own on-page SEO across PDPs, PLPs, content hubs, comparison pages, category pages, buying guides, landing pages, and editorial content. • Build and execute internal linking strategies that improve crawl efficiency, topical authority, product discovery, and customer journeys. • Define and track SEO KPIs — organic sessions, rankings, impressions, CTR, revenue contribution, non-brand growth, technical health, indexation, crawl efficiency, and AI/citation visibility. • Create scalable SEO frameworks that can be applied consistently across Resident brands, Ashley portfolio brands, and Newton Baby.