4 days ago
Prague, CzechiaMid Level
Responsibilities
- Collaborate with cross-functional technical and business teams to understand requirements and develop machine learning solutions.
- Develop and deploy batch-based machine learning products and real-time ML/AI services in cloud environments.
- Create MLOps automation processes using ETL data pipelines to improve model performance, data collection, and preparation.
- Advocate for best practices and architecture in ML/LLM Ops.
- Document analytical processes, methodologies, and findings for reproducibility and knowledge sharing.
Requirements
- Master’s degree in a STEM field such as Computer Science, Machine Learning/AI, Physics, Engineering, or a similar discipline.
- At least 3 years of experience building and deploying production-scale machine learning models that deliver measurable business value.
- Strong understanding of modern machine learning and LLM-enabled pipelines, hybrid ML architectures, and agentic workflows.
- Practical experience with PyTorch, NumPy, Pandas, scikit-learn, SciPy, XGBoost, or similar frameworks.
- Strong SQL and Python programming skills.
- Experience with AWS Redshift, Git or GitLab, ETL pipelines, automated retraining, benchmarking, and evaluation.
- Preferred: PhD in a STEM field; financial or commercial industry experience; AWS Bedrock, Ray RLlib, vLLM, Apache Spark, Gym, OpenRLHF, Stable Baselines, PyTorch RL, FastAPI, or Starlette experience.
- Strong communication, prioritization, self-management, attention to detail, and interest in current AI/ML research.
Benefits
- Prague-based hybrid work with an assigned office workspace, company-issued equipment, and formal hands-on training.
- 25 vacation days pro-rated, 3 sick days, 2 additional days after vacation is used, and 2 volunteer days.
- Variable benefits allowance of 15,600 CZK per year for options including Multisport, retirement insurance contributions, or a cafeteria benefits account.
- Workplace massages with half the cost covered, discounted T-Mobile tariffs, milestone and wedding gifts, referral bonuses, birthday breakfast, sports activities, online educational courses, fresh fruit, and a Christmas party.
Tech Stack
Categories
