Role Description We are seeking a Machine Learning Engineer to develop, train, and deploy ML models that power our core product features. You will bridge the gap between data science research and production-ready systems. Key Responsibilities - Design and implement ML pipelines from data ingestion to model deployment. - Work with data scientists to bring models into production. - Monitor model performance and implement retraining strategies. - Collaborate with backend engineers to integrate ML services. - Stay current with advances in ML research and tooling. Requirements - 3+ years of ML engineering or data science experience. - Proficiency in Python and ML frameworks (TensorFlow, PyTorch, or scikit-learn). - Experience with MLOps tools and cloud ML platforms. - Strong understanding of statistics and model evaluation. - Ability to communicate technical concepts clearly.

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 $90 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 $90 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 $90 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.