About the role
structured by ORIAbout the Role Woodfrog is hiring Software Engineers – NLP/LLM Reasoning for one of our deep-tech clients building advanced reasoning models for enterprise applications using Large Language Models (LLMs) . This is an opportunity to work at the intersection of cutting-edge AI research and production engineering,…
What you will do
- Design, develop, and optimize foundational reasoning models for enterprise applications.
- Research and implement advanced NLP techniques and reasoning paradigms.
- Build, maintain, and improve production-ready AI systems powered by Large Language Models.
- Write clean, efficient, scalable, and well-documented Python code.
- Collaborate with product, engineering, and research teams to define technical solutions.
What they are looking for
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Linguistics, or a related field.
- Strong programming skills in Python.
- Hands-on experience with Natural Language Processing (NLP) and Large Language Models (LLMs).
- Experience with TensorFlow, PyTorch, or similar deep learning frameworks.
- Good understanding of transformer architectures, prompt engineering, embeddings, and reasoning techniques.
- Strong analytical, debugging, and problem-solving skills.
- Excellent communication and collaboration abilities.
- Ability to work independently in a high-ownership, fast-paced environment.
Nice to have
- Experience with Retrieval-Augmented Generation (RAG), Vector Databases, or Agentic AI.
- Familiarity with LLM fine-tuning, evaluation, and optimization.
- Experience deploying AI models in production environments.
- Knowledge of cloud platforms such as AWS, Azure, or GCP.
Full posting text
About the Role Woodfrog is hiring Software Engineers – NLP/LLM Reasoning for one of our deep-tech clients building advanced reasoning models for enterprise applications using Large Language Models (LLMs) . This is an opportunity to work at the intersection of cutting-edge AI research and production engineering, developing intelligent systems that solve complex real-world business problems.
As a Software Engineer, you will be responsible for designing, developing, and optimizing enterprise-grade reasoning models while researching innovative NLP techniques and integrating them into scalable production systems. You will collaborate with cross-functional teams to deliver high-quality AI solutions, maintain clean and efficient code, and continuously improve model performance.
This role is best suited for engineers who enjoy solving challenging problems, thrive in fast-paced startup environments, and are passionate about advancing the capabilities of LLMs and reasoning systems.
Key Responsibilities Design, develop, and optimize foundational reasoning models for enterprise applications.
Research and implement advanced NLP techniques and reasoning paradigms.
Build, maintain, and improve production-ready AI systems powered by Large Language Models.
Write clean, efficient, scalable, and well-documented Python code.
Collaborate with product, engineering, and research teams to define technical solutions.
Monitor, troubleshoot, and improve model performance and system reliability.
Stay up to date with the latest developments in NLP, LLMs, and AI research, and apply them to real-world products.
Required Skills & Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Linguistics, or a related field.
Strong programming skills in Python .
Hands-on experience with Natural Language Processing (NLP) and Large Language Models (LLMs) .
Experience with TensorFlow , PyTorch , or similar deep learning frameworks.
Good understanding of transformer architectures, prompt engineering, embeddings, and reasoning techniques.
Strong analytical, debugging, and problem-solving skills.
Excellent communication and collaboration abilities.
Ability to work independently in a high-ownership, fast-paced environment.
Preferred Qualifications Experience with Retrieval-Augmented Generation (RAG), Vector Databases, or Agentic AI.
Familiarity with LLM fine-tuning, evaluation, and optimization.
Experience deploying AI models in production environments.
Knowledge of cloud platforms such as AWS, Azure, or GCP.
Seniority level: Entry level
Employment type: Full-time
Industries: IT System Data Services