Data Science/AI ML Engineer (AI)

TL;DR

Data Science/AI ML Engineer (AI/ML): Building specialized Large Language Models (LLMs) to deliver commercial-grade intelligence with an accent on model internals, tensor operations, and architecture design. Focus on translating research papers into production-ready implementations and optimizing inference costs.

Location: Budapest (Flexible)

Company

AI-powered Experience Orchestration platform empowering organizations to create superior customer and employee experiences.

What you will do

• Design and implement specialized LLMs, focusing on model weights, attention mechanisms, and sparse architectures.
• Translate research papers into prototypes and reusable Python libraries.
• Build and maintain evaluation frameworks to compare model intelligence, reasoning, and inference costs.
• Support and optimize cloud infrastructure utilizing AWS SageMaker, S3, and GPU instances.
• Engage with the open-source ML ecosystem and contribute to the team's research agenda.

Requirements

• Degree in Computer Science, ML, Mathematics, or equivalent hands-on experience.
• 3+ years in ML engineering, with at least 1 year working directly with LLMs or deep learning architectures.
• Proficiency in Python and PyTorch, and experience with HuggingFace Transformers.
• Experience with AWS services for ML workloads (SageMaker, EC2 GPU, S3).
• Strong software engineering practices, including Git, CI/CD, and unit testing.

Nice to have

• Exposure to sparse architectures, expert routing, or model compression techniques (quantization).
• Experience with Infrastructure as Code (IaC) tools like CloudFormation or Terraform.
• Familiarity with conversational AI or the contact center industry.

Culture & Benefits

• Work on novel research that directly influences AI systems used by millions globally.
• Clear paths toward technical leadership and freedom to explore research directions.
• Remote-friendly environment with flexible working arrangements.
• Culture based on mutual respect, psychological safety, and diversity.