ML Engineer

Link Group is seeking a Machine Learning Engineer to design, develop, and deploy scalable ML solutions in a cloud-based environment, working at the intersection of machine learning, data engineering, and knowledge graph technologies.

• Strong experience with Python for machine learning and data processing.
• Experience building and deploying machine learning models in production.
• Knowledge of MLOps practices, including CI/CD for ML systems.
• Experience with NLP techniques, including NER and RAG.
• Understanding of Knowledge Graphs and semantic technologies (RDF/SPARQL).
• Experience with SQL and data engineering concepts (ETL/ELT).
• Experience with Google Cloud Platform, particularly Vertex AI, Dataflow, and GKE.
• Experience with distributed computing frameworks such as Ray.
• Familiarity with vector databases and semantic search architectures.
• Knowledge of GPU computing and CUDA for ML acceleration.
• Strong communication skills and English proficiency at C1 level.
• Experience working in Agile development environments.

• Design, develop, and deploy machine learning models and AI-driven solutions.
• Build and maintain data pipelines and ETL/ELT processes for ML workflows.
• Implement MLOps practices, including CI/CD for machine learning pipelines and model deployment.
• Work with NLP techniques, including Named Entity Recognition (NER) and Retrieval-Augmented Generation (RAG).
• Develop and integrate knowledge graph–based solutions using RDF/SPARQL.
• Work with vector databases to support semantic search and ML-driven applications.
• Deploy and manage ML workloads in Google Cloud Platform (GCP) using services such as Vertex AI, Dataflow, and GKE.
• Utilize distributed computing frameworks such as Ray and HPC environments for large-scale model training.
• Optimize model performance using GPU acceleration (CUDA).
• Collaborate with cross-functional teams in an Agile development environment.