• Provide input on the future direction of new assessment solutions and roadmaps for existing tests and assessment products, including enhancements, upgrades, and new applications. • Design, develop, refine, and integrate innovative content, methods, and scoring approaches for leadership tests, simulations, and other assessment solutions. • Identify and develop ways to integrate assessments into the learning and development process (e.g., a test linked to a learning experience). • Maintain and enhance existing tests and assessment products through ongoing monitoring, evaluation, and refresh efforts. • Manage and conduct validation studies for newly developed and existing assessment solutions, including analyses of reliability, validity, subgroup differences, fairness, and practical utility. • Analyze cross-client datasets to develop norms, benchmarks, and score interpretation frameworks. • Ensure assessment solutions align with professional testing standards, fairness expectations, and applicable legal and ethical guidelines. • Write technical documentation and research reports. • Design feedback reports and score interpretation resources that promote user insight, development, and action planning. • Present analytical findings and research insights to both technical and non-technical audiences. • Serve as a thought leader on leadership testing, assessment, and development topics through conference presentations, white papers, and other external-facing contributions. • Partner with cross-functional teams, including product, consulting, and technology partners, to support implementation and scale assessment solutions effectively.

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 graduate- and industry-level automotive engineering problems grounded in real practice; - Evaluate AI-generated solutions for correctness, assumptions, and engineering logic; - Validate analytical or numerical results using Python (NumPy, SciPy, Pandas); - Improve AI reasoning to align with first principles and accepted engineering standards; - Apply structured scoring criteria to assess multi-step problem solving. What we look for This opportunity is a good fit for automotive engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  - Degree in Automotive Engineering or related fields, e.g. Mechatronics, Manufacturing Engineering, Mechanical Engineering, Aerospace Engineering, etc. - 3+ years of professional automotive engineering experience - Strong written English (C1/C2) - Strong Python proficiency for numerical validation - Stable internet connection  Professional certifications (e.g., PE, CEng, PMP) and experience in international or applied projects are an advantage. 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 $55 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 the design, development and deployment of Machine Learning models to solve business problems. • Develop and maintain clean, efficient, and scalable code that meets industry standards. • Analyze large datasets to extract actionable insights and make informed decisions. • Employ state-of-the-art Machine Learning methodologies and frameworks to develop robust and scalable models. • Influence technical direction and take ownership of key components of systems and solutions, ensuring that they meet the needs of the business. • Collaborate with key stakeholders in the development of data-driven solutions and deployable products. • Mentor and guide team members to help establish team domain expertise. • Contribute to the company’s intellectual property and technical leadership through patents and publications at top-tier conferences and journals.

Lead interdisciplinary project teams to develop and implement clinical pharmacology strategies, ensuring project timelines and objectives are met while providing expert input on drug candidates throughout their development lifecycle.