Senior LLM Engineer – Text & Reasoning LLM, NLU

This is a fully remote position, open to applicants in Greece.

📋 Description

• Lead research initiatives and experimentation focused on innovative model architectures, training techniques, and evaluation methods for LLM/NLU.

• Design, develop, fine-tune, and assess specialized LLMs tailored for Concierge and Task Agents.

• Create and optimize ML pipelines for the training, evaluation, and deployment processes utilizing AWS SageMaker.

• Architect and manage inference servers to ensure low latency and high reliability.

• Implement and enhance closed-loop self-learning systems aimed at continuous model enhancement.

• Drive the benchmarking process, ensure experiment reproducibility, and maintain documentation quality.

• Ensure adherence to data privacy standards throughout the entire ML lifecycle.

• Mentor and facilitate the development of team members, sharing knowledge through tech talks and guides.

⛳️ Requirements

• A minimum of 5 years of experience in applied LLM/ML/NLU/NLP, with a proven track record of managing production ML systems at scale.

• Strong practical expertise in Python, PyTorch, and HuggingFace Transformers.

• Extensive experience with LLMs, including fine-tuning, distillation, prompt engineering, evaluation, and deployment, particularly with small/efficient models.

• Solid understanding of NLU concepts such as intent classification and entity extraction.

• Familiarity with model serving infrastructures like Triton Inference Server, vLLM, TGI, and FastAPI.

• Experience with cloud ML infrastructures such as AWS SageMaker, Bedrock, or equivalent platforms.

• Demonstrated ability in architectural decision-making and technical ownership across various services/products.

• Competence in deconstructing ambiguous challenges and formulating actionable plans.

• Exceptional communication skills suitable for both technical and non-technical audiences.

• Nice to Have:

• Experience in designing agentic systems (e.g., tool use, reasoning chains, multi-step planning).

• Background in self-learning/continuous improvement ML systems.

• Multilingual NLU or experience with cross-lingual transfer.

• Knowledge of PCI/PII compliance within ML workflows.

• Familiarity with experiment tracking tools such as Weights & Biases or MLflow.

• Contributions to open-source ML/NLP projects or publications in leading venues.

• Experience with speech or multimodal LLMs.

🏝️ Benefits

• Fixed compensation;

• Long-term employment with vacation days;

• Opportunities for professional development (courses, training, etc.);

• Participation in innovative technology products that are making a significant global impact in the service industry;

• Engaging and enjoyable colleagues;

• Apple equipment provided.