Please submit your CV in English and indicate your level of English proficiency. 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 While each project involves unique tasks, contributors may:  - Design original computational mathematics problems that simulate real mathematical research workflows; - Create problems requiring Python programming to solve (using Numpy, SciPy, Sympy); - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks); - Develop problems requiring non-trivial reasoning chains in areas like number theory, combinatorics, graph theory, and numerical analysis; - Base problems on real research challenges or practical applications from mathematical practice; - Verify solutions using Python with standard mathematical libraries; - Document problem statements clearly and provide verified correct answers. What we look for This opportunity is a good fit for mathematicians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:   - Degree in Mathematics (Pure or Applied) or related fields; - Python proficiency for numerical validation. MATLAB, R, C, SQL, Numpy, Pandas, SciPy, domain-specific libraries, Stata or knowledge of any programming language can be equivalent; - 2+ years of professional experience: applied, research, or teaching experience is applicable; - Experience with numerical methods and symbolic computation; - Ability to design problems that mirror real mathematical research workflows; - Familiarity with computational complexity theory; - Strong written English (C1+). How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, 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. Compensation On this project, contributors can earn up to $76 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.

Please submit your CV in English and indicate your level of English proficiency. 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 While each project involves unique tasks, contributors may:  - Design original computational mathematics problems that simulate real mathematical research workflows; - Create problems requiring Python programming to solve (using Numpy, SciPy, Sympy); - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks); - Develop problems requiring non-trivial reasoning chains in areas like number theory, combinatorics, graph theory, and numerical analysis; - Base problems on real research challenges or practical applications from mathematical practice; - Verify solutions using Python with standard mathematical libraries; - Document problem statements clearly and provide verified correct answers. What we look for This opportunity is a good fit for mathematicians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:   - Degree in Mathematics (Pure or Applied) or related fields; - Python proficiency for numerical validation. MATLAB, R, C, SQL, Numpy, Pandas, SciPy, domain-specific libraries, Stata or knowledge of any programming language can be equivalent; - 2+ years of professional experience: applied, research, or teaching experience is applicable; - Experience with numerical methods and symbolic computation; - Ability to design problems that mirror real mathematical research workflows; - Familiarity with computational complexity theory; - Strong written English (C1+). How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, 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. Compensation On this project, contributors can earn up to $76 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.

Please submit your CV in English and indicate your level of English proficiency. 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 While each project involves unique tasks, contributors may:  - Design original computational mathematics problems that simulate real mathematical research workflows; - Create problems requiring Python programming to solve (using Numpy, SciPy, Sympy); - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks); - Develop problems requiring non-trivial reasoning chains in areas like number theory, combinatorics, graph theory, and numerical analysis; - Base problems on real research challenges or practical applications from mathematical practice; - Verify solutions using Python with standard mathematical libraries; - Document problem statements clearly and provide verified correct answers. What we look for This opportunity is a good fit for mathematicians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:   - Degree in Mathematics (Pure or Applied) or related fields; - Python proficiency for numerical validation. MATLAB, R, C, SQL, Numpy, Pandas, SciPy, domain-specific libraries, Stata or knowledge of any programming language can be equivalent; - 2+ years of professional experience: applied, research, or teaching experience is applicable; - Experience with numerical methods and symbolic computation; - Ability to design problems that mirror real mathematical research workflows; - Familiarity with computational complexity theory; - Strong written English (C1+). How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, 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. Compensation On this project, contributors can earn up to $76 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.

• AI Workflow Development & Prompt Engineering • Design, develop, and iterate AI workflows tailored to specific practice areas and legal use cases, testing outputs for accuracy, consistency, and alignment with legal standards and client expectations. • Partner with attorneys, KMI Attorneys, and IT teams to understand legal processes and translate them into effective AI-enabled solutions using firm-approved tools. • Document prompt libraries, workflow configurations, and best practices to enable scalability and knowledge sharing across the firm. • Continuously evaluate and improve existing AI workflows based on user feedback, evolving AI capabilities, and changing practice needs. • Practice Group Collaboration • Serve as a resource to practice groups, understanding their unique workflows, pain points, and opportunities for AI-driven improvement. • Conduct intake sessions with attorneys to identify high-value use cases and prioritize AI initiatives based on impact and feasibility. • Collaborate with KMI Attorneys and practice service centers to ensure AI solutions align with existing knowledge resources, templates, and practice standards. • Translate complex legal requirements into technical specifications for AI workflows, ensuring outputs meet the substantive needs of each practice area. • Quality Assurance & Compliance • Test AI outputs for accuracy, completeness, and adherence to legal, ethical, and alignment with firm standards. • Support compliance with firm AI governance policies in all AI implementations. • Document testing protocols, outcomes, and lessons learned; identify and escalate risks as appropriate. • Stay current on AI developments, regulatory changes, and industry best practices; share relevant insights with the KMI team. • Training & Adoption Support • Collaborate with training and knowledge management teams to develop resources that help attorneys effectively use AI tools. • Contribute to adoption initiatives by gathering user feedback and sharing insights that inform tool improvements and training approaches. • Support attorneys in integrating AI solutions into their workflows through responsive guidance and troubleshooting. • Project Support & Reporting • Coordinate tasks, timelines, and stakeholders for AI workflow development initiatives. • Track and report project status, adoption metrics, and outcomes to KMI leadership. • Contribute to the development of scalable playbooks and processes that support the growth of the legal engineering function.