FREE ACCESS
5,000–10,000 jobs/day
See all jobs on JobTailor
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
MLOps – Machine Learning Engineer
GTO WizardMLOps Engineer developing the infrastructure for machine learning systems at GTO Wizard. Focused on building and optimizing large-scale distributed training and evaluation platforms.
Tech Stack
Tools & technologiesCloudPyTorch
About the role
Key responsibilities & impact- Build and maintain large-scale distributed training and evaluation pipelines for Deep Reinforcement Learning.
- Design scalable infrastructure for training, evaluation, model management, and experiment tracking.
- Build dashboards and monitoring tools to track training progress, model quality, compute usage, and agent performance.
- Optimize the training and inference performance of our Deep Learning models.
- Improve cost efficiency across cloud/GPU infrastructure and make high-impact infrastructure decisions.
- Work closely with researchers and engineers to reduce iteration time and improve model accuracy.
- Help design reproducible ML workflows, including data pipelines, checkpointing, evaluation, versioning, and deployment.
- Identify bottlenecks across the full ML stack: model architecture, data loading, GPU utilization, distributed training, inference, and infrastructure.
- Contribute directly to ML improvements that increase accuracy, robustness, and compute efficiency.
Requirements
What you’ll need- Strong software engineering skills and experience building reliable production-quality systems.
- Hands-on experience with PyTorch or similar deep learning frameworks.
- Experience building infrastructure for machine learning training and evaluation.
- Experience with distributed training at scale across GPUs or clusters.
- Strong understanding of ML training workflows, model evaluation, experiment tracking, and performance monitoring.
- Ability to optimize systems for speed, reliability, and cost efficiency.
- Applied ML or ML infrastructure experience with a successful track record of delivering quality results.
- Exceptional communication, cross-discipline collaboration, and leadership skills.
- Passion for games and how intelligent systems can teach humans problem-solving skills.
Benefits
Comp & perks- Impactful Work: Be part of a company that's transforming how poker is studied and played worldwide.
- Innovative Environment: Work with cutting-edge technology and contribute to a platform that's pushing the boundaries of poker strategy.
- Professional Growth: We support your personal and professional development with opportunities to learn new skills and take on exciting challenges.
- Collaborative Culture: Join a team where your ideas are valued, and you can make a real impact in a supportive, inclusive environment.
- Flexible Work Arrangements: Enjoy the benefits of remote work while collaborating with a global team.
- Passionate Community: Engage with a vibrant community of poker enthusiasts and professionals who are passionate about the game.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Deep Reinforcement LearningPyTorchmachine learning trainingdistributed trainingmodel evaluationexperiment trackingperformance monitoringdata pipelinescheckpointingmodel management
Soft Skills
communicationcross-discipline collaborationleadershipproblem-solving