• Build and optimize the systems infrastructure behind large-scale RL and distributed training workloads. • Improve end-to-end training efficiency across compute, memory, networking, and scheduling layers. • Design and implement low-level performance optimizations, including kernels, communication paths, and runtime improvements. • Work on distributed training systems spanning data, tensor, and pipeline parallel workloads. • Help shape the architecture of our RL training stack, including async rollout and post-training systems. • Contribute to open-source libraries and internal infrastructure used for frontier-scale model training. • Collaborate closely with researchers and infrastructure engineers to translate bottlenecks into concrete systems improvements. • Stay at the frontier of training systems, inference systems, compiler/runtime tooling, and hardware-aware optimization techniques.

• Creating and upholding a reliable and expandable data management system specialized for text-to-speech projects. This includes establishing guidelines for versioning and ensuring data quality. • Establishing a streamlined process for autonomously training, assessing, and launching text-to-speech models. This encompasses implementing procedures for dynamic learning, as well as routines for fine-tuning and refreshing validation data. • Investigating cutting-edge approaches and strategies in machine learning, deep learning, and algorithms pertaining to text-to-speech technology.

• We are looking for someone who not only observes technical innovations but actively integrates them into our infrastructure. • You support the team responsible for infrastructure, DevOps and technical automation. • A particularly important part of your role is close collaboration with the Team Lead: you assist in preparing technical decisions, rapid prototyping and the rollout of new tools—especially AI-based solutions. • Develop our infrastructure further—you expand our deployment environments and automate where it noticeably improves stability, speed and transparency in everyday work. • Shape the DevOps culture—you take ownership of CI/CD, observability and security topics in the team’s day-to-day operations and ensure smooth processes. • Be a sparring partner for the Team Lead—you work closely with the Team Lead daily on architecture, workflows and current operational issues. • Pragmatically validate innovations—you use rapid prototyping to quickly test new ideas and technologies and assess their value for us. • Drive AI tools forward—you introduce new AI solutions, support onboarding and empower your colleagues through training and best practices.

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 chemistry problems that simulate real chemistry research workflows; - Create problems requiring Python programming to solve (using numpy, scipy, chemical libraries); - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks); - Develop problems requiring non-trivial reasoning chains in physical chemistry, quantum chemistry, and molecular modeling; - Base problems on real research challenges or practical applications from chemistry practice; - Verify solutions using Python with standard computational chemistry approaches; - Document problem statements clearly and provide verified correct answers. What we look for This opportunity is a good fit for chemistry specialists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:   - Degree in Chemistry 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 in chemistry; - Familiarity with computational chemistry concepts and methods; - 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 $26 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.