Senior AI/ML Engineer - Generative AI Specialist, iGaming Department

EGT Digital is a next-generation tech company focused on all online gaming products, and its portfolio includes Casino Games, Sportsbook, and the all-in-one solution - a Gambling Platform. EGT Digital is a part of the Euro Games Technology (EGT) Group, headquartered in Sofia, Bulgaria. EGT Group is one of the fastest-growing enterprises in the gaming industry. Our global network includes offices in 25 countries and our products are installed in over 85 European jurisdictions, Asia, Africa, North, Central, and South America jurisdictions. Being a part of such a fast-moving industry as iGaming, the company knows no limits and is growing rapidly through its dedication to innovation and constant improvement. This is why we are expanding our iGaming Department and now looking for some fresh and enthusiastic people to come and join us in the exciting digital world of iGaming. The Role As our Senior AI/ML Engineer, you will be responsible for architecting, developing, and optimizing our generative AI infrastructure. This role requires expertise across the entire machine learning lifecycle, from data preparation and model development to deployment and monitoring in production environments. Responsibilities: Design and implement scalable, high-performance infrastructure for training and serving large language models (LLMs) Develop and optimize model serving pipelines, focusing on low-latency inference and efficient resource utilization Create robust APIs and integrate AI capabilities into our existing software stack Implement advanced NLP techniques, including but not limited to, few-shot learning, prompt engineering, and Retrieval-Augmented Generation (RAG) Lead the fine-tuning and adaptation of pre-trained models to our specific domains and use cases Design and implement evaluation frameworks to measure model performance and ensure output quality Collaborate with cross-functional teams to identify AI integration opportunities and drive innovation Requirements: University Degree in Computer Science, Machine Learning, or a related field 5+ years of experience in machine learning, with a focus on NLP and deep learning Extensive experience with PyTorch or TensorFlow, and familiarity with Hugging Face Transformers Proficiency in Python and experience with ML ops tools (e.g., MLflow, Kubeflow) Strong background in optimizing model inference (e.g., quantization, distillation, ONNX runtime) Experience with distributed training and large-scale model serving architectures Familiarity with vector databases and embedding techniques Solid understanding of software engineering best practices, including version control, CI/CD, and containerization Preferred Qualifications Experience with transformer architectures and attention mechanisms Familiarity with reinforcement learning, particularly in the context of language models (e.g., RLHF) Knowledge of prompt engineering techniques and in-context learning Experience with cloud platforms (AWS, GCP, or Azure) and their ML-specific offerings Understanding of AI ethics, bias mitigation, and responsible AI development practices Contributions to open-source ML projects or research publications in NLP/ML Technical Stack Languages: Python, C++ (for optimization) Frameworks: PyTorch or TensorFlow, Hugging Face Transformers Infrastructure: Docker, Kubernetes Cloud: AWS SageMaker, AWS Bedrock, Azure ML, or Google Cloud AI Platform Databases: PostgreSQL, Apache Cassandra, MongoDB, Redis What we offer Competitive salary Performance evaluation 25 days paid annual leave Work from home option -2 days weekly Flexible working schedule Additional health insurance – premium package Fully paid annual transportation card Fully paid Sports card Free company shuttle by the office Sports Teams & sports events Professional development Company-sponsored trainings Tickets for conferences and seminars Team building events and office parties Referral Program Free snacks, soft drinks, coffee, and fruit - always available Newborn baby bonus Corporate discounts in various shops and restaurants Thanks for taking the time to apply! Your application will be kept fully confidential - we'll reach out personally if you're shortlisted for an interview.