Senior NLP Engineer
Tasks
- Apply direct preference optimization
- Apply reinforcement learning from human feedback
- Build agentic frameworks
- Build backend systems for high throughput inference
- Design experiments and measure results
- Evaluate model quality and performance
- Fine-tune large language models
- Implement Reasoning Loops
- Optimize language model performance
- Orchestrate chat systems
- Own LLM lifecycle from data prep to deployment
- Research NLP techniques for product roadmap
- Run production monitoring for LLMs
- Train large language models
Perks/Benefits
- Conference support
- English learning discounts
- Fully remote
- Health support budget
- Home-office allowance
- Paid vacation
- Performance bonuses
- Professional development support
- Wellness days
Skills/Tech-stack
Agent Frameworks | C# | Chat orchestration | Direct Preference Optimization | Distributed Training | Fine Tuning | Go | High Throughput | High-Throughput Systems | Human Feedback | LLM orchestration | Language Models | Language Processing | Large Language Models | Learning from Human Feedback | Machine Learning | Model Fine-tuning | Natural Language | Natural Language Processing | Preference optimization | PyTorch | Python | Reasoning loops | Reinforcement Learning | Reinforcement Learning from Human Feedback | Transformer Architecture
Education
N/A
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