4 days ago
Prague, CzechiaStaff+
Responsibilities
- Lead the design, implementation, and maintenance of scalable, reliable, and cost-effective AI platform solutions in the cloud.
- Translate AI Research model requirements into scalable infrastructure and production systems.
- Improve data pipelines, feature storage, experiment tracking, and model lifecycle workflows.
- Build tooling for experimentation, benchmarking, and reproducibility.
- Implement monitoring, observability, and reliability improvements across AI services.
- Contribute to architecture discussions, long-term platform strategy, and cross-functional alignment with Product and Research.
- Maintain documentation and support knowledge-sharing across R&D.
Requirements
- 5+ years of experience in product-minded software engineering, ML platform engineering, or infrastructure roles.
- Demonstrated ability to lead technical teams, maintain focus, and navigate challenging situations.
- Proven delivery of ML solutions with measurable business and customer impact.
- Strong programming experience in Python or another language suitable for ML.
- Understanding of distributed systems, microservices, and cloud-native architectures.
- Experience with SQL databases, including query optimization, performance tuning, and schema design.
- Experience with ML tooling such as experiment tracking, model registries, and data pipelines.
- Strong problem-solving skills and experience working in cross-functional R&D environments.
- Understanding of CI/CD, infrastructure-as-code, and observability tooling.
- Experience training or serving AI/ML models at scale is preferred.
- Experience with scalable automated ETL/ELT pipelines, SQL/NoSQL database architectures, data annotation, dataset management, GPU workloads, batch or stream processing, or feature stores is preferred.
- Exposure to Intelligent Document Processing or Deep Neural Network architectures is preferred.
- Professional internal communication in English.
Benefits
- 33 days off including PTO, personal days, a birthday day, and two company wellness days.
- Parental leave in addition to the standard time-off allowance.
- Prague Karlín workspace with full technology setup and a 200 m² terrace.
- Access to frontier LLMs, high-end GPUs, and large-memory clusters for training.
- Opportunity to work on proprietary in-house T-LLM architectures and systems used globally.
Tech Stack
Categories
