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 STEM problems that simulate real scientific workflows - Create problems that require Python programming to solve - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks) - Develop problems requiring non-trivial reasoning chains and creative problem-solving approaches - Verify solutions using Python with standard libraries (Numpy, Pandas, Scipy, scikit-learn) - Document problem statements clearly and provide verified correct answers What we look for This opportunity is a good fit for ML specialists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:   - 5+ years of hands-on machine learning experience with proven business impact - Portfolio of completed projects and publications showcasing real-world problem-solving - Expert Python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels) - Expert statistical analysis and machine learning - deep understanding of algorithms, methods, and their practical applications - Expert with SQL and database operations for data manipulation and analysis - Experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases) - Understanding of MLOps practices and model deployment workflows - Knowledge of modern frameworks (TensorFlow, PyTorch, LangChain) - 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 $58 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 STEM problems that simulate real scientific workflows - Create problems that require Python programming to solve - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks) - Develop problems requiring non-trivial reasoning chains and creative problem-solving approaches - Verify solutions using Python with standard libraries (Numpy, Pandas, Scipy, scikit-learn) - Document problem statements clearly and provide verified correct answers What we look for This opportunity is a good fit for ML specialists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:   - 5+ years of hands-on machine learning experience with proven business impact - Portfolio of completed projects and publications showcasing real-world problem-solving - Expert Python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels) - Expert statistical analysis and machine learning - deep understanding of algorithms, methods, and their practical applications - Expert with SQL and database operations for data manipulation and analysis - Experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases) - Understanding of MLOps practices and model deployment workflows - Knowledge of modern frameworks (TensorFlow, PyTorch, LangChain) - 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 $58 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 STEM problems that simulate real scientific workflows - Create problems that require Python programming to solve - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks) - Develop problems requiring non-trivial reasoning chains and creative problem-solving approaches - Verify solutions using Python with standard libraries (Numpy, Pandas, Scipy, scikit-learn) - Document problem statements clearly and provide verified correct answers What we look for This opportunity is a good fit for ML specialists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:   - 5+ years of hands-on machine learning experience with proven business impact - Portfolio of completed projects and publications showcasing real-world problem-solving - Expert Python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels) - Expert statistical analysis and machine learning - deep understanding of algorithms, methods, and their practical applications - Expert with SQL and database operations for data manipulation and analysis - Experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases) - Understanding of MLOps practices and model deployment workflows - Knowledge of modern frameworks (TensorFlow, PyTorch, LangChain) - 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 $58 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.

• Support the development, training, and evaluation of ML/AI models using Python and industry-standard frameworks • Apply supervised learning techniques such as Logistic Regression, Gradient Boosting Machines (GBM), and Random Forests to solve classification and regression problems • Explore and implement Generative AI models (e.g., transformers, diffusion models) for use cases such as text generation, summarization, or synthetic data creation • Analyze structured and unstructured datasets using pandas, NumPy, and matplotlib/seaborn for data wrangling and visualization • Use scikit-learn, XGBoost, and TensorFlow/PyTorch to build and validate predictive models • Contribute to software development projects using Python, Java, or Kotlin • Present findings, model performance, and project outcomes to teams • Participate in code reviews, team meetings, and brainstorming sessions to support collaborative innovation