Hover or tap a row for full statistics (EUR / month on this chart).
Salary analysis
Compared with the selected benchmark ("Company in Remote - Europe"), this listing's salary midpoint is about 89% lower. The offer sits below the benchmark range (€1,667–€6,000). The listed pay band (€319–€500) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 6 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| All roles in Remote - Europe | €1,978/per month | €4,914/per month | €13,713/per month |
| Company in Remote - Europe | €1,667/per month | €2,056/per month | €6,000/per month |
| This job's pay range — not quoted in ad (Senior) | €319/per month | €410/per month | €500/per month |
The role is for Nebius AI R&D, a team focused on applied research in AI. The role includes conducting experiments to train large language models, exploring guided generation and search, mining data at web scale, and evaluating RL configurations. Requirements include deep knowledge of ML and RL, expertise in deep learning for language, experience with training large models, strong Python skills, and ability to document and publish findings. Nice to have: RL for LLMs, RoPE/Zero-FSDP/Flash Attention, higher degrees, startup experience, open-source work, strong English proficiency. Benefits & Perks listed include competitive compensation, growth opportunities, flexibility, collaborative culture, impactful AI projects, international environment. Nebius emphasizes equal opportunity and encourages diverse applicants.
Job Details
Responsibilities
- Conducting experiments to train a large language model on traces of interactions with various environments
- Exploring guided generation and search in the trajectory space
- Mining relevant data at web scale and using it in model post-training
- Conducting experiments with different reinforcement learning configurations in verifiable domains
- Exploring methods to train AI agents on tasks with non-verifiable reward signals
Requirements
- A profound understanding of theoretical foundations of machine learning and reinforcement learning
- Deep expertise in modern deep learning for language processing and generation
- Substantial experience with training large models on multiple computational nodes
- Strong software engineering skills (we mostly use python)
- Deep experience with modern deep learning frameworks (we use jax)
- Strong communication and leadership abilities
- Experience designing, executing, and analyzing machine learning experiments with proper statistical rigor
- Ability to formulate research questions, design experiments to test hypotheses, and draw meaningful conclusions from results
- Ability to document research findings clearly and contribute to technical publications or report
Skills & Technologies
Education Level
Bachelor
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