Senior AI Engineer

Link Group is seeking a Senior AI Engineer to join a team focused on developing and deploying machine learning solutions to improve engineering processes and operational performance in a global automotive environment.

• Master’s degree in Computer Science, Machine Learning, or a closely related technical field
• 5+ years of experience developing and deploying machine learning systems in production
• Strong background with cloud platforms (AWS, Azure) including data processing, training, and deployment services
• Proficient in Python and ML frameworks/libraries such as PyTorch, TensorFlow, scikit-learn
• Deep understanding of machine learning system architecture including data pipelines, model lifecycle management, and performance optimization
• Experience with MLOps tools and best practices (MLflow, Kubeflow, SageMaker)
• Familiarity with LLMs, prompt engineering, and inference optimization in generative AI
• Solid software engineering fundamentals including object-oriented programming, version control, testing, and writing clean code
• Ability to work independently and collaboratively in a fast-paced, cross-functional team environment

• Analyze technical and business requirements to architect effective AI/ML solutions
• Develop and deploy production-ready machine learning models ensuring scalability, performance, and maintainability
• Explore and evaluate new algorithms and techniques including Large Language Models (LLMs) and Generative AI for integration
• Build and maintain end-to-end data and model pipelines including data ingestion, training, validation, and serving
• Continuously monitor deployed systems for performance and reliability and iterate for improved outcomes
• Support development and adoption of MLOps practices such as reproducibility, CI/CD for ML workflows, and automated monitoring
• Collaborate with data scientists, software engineers, and ML professionals to deliver high-quality AI solutions
• Stay informed on emerging AI/ML research and developments, focusing on generative models and practical applications