Job Overview
Company logo: https://media.licdn.com/dms/image/v2/C4D0BAQGHeQsU54NLQA/company-logo_400_400/company-logo_400_400/0/1663258479025/ascendion_logo?e=1749081600&v=beta&t=XGva-oNMh0fh3ukE9t8rRqIkjAakP_uFqmuCbYbP_is Role OverviewWe are seeking a Software Development Engineer (SDE) with a strong background in Generative AI and Knowledge Graphs to help design, develop, and deploy state-of-the-art AI-powered systems. As an SDE in our team, you will contribute to projects that leverage deep learning models, natural language processing (NLP), and graph databases to enable smarter decision-making and automation for our products and services.
Key ResponsibilitiesSoftware Development: Develop and optimize scalable, robust, and high-performance software solutions that leverage Generative AI and Knowledge Graphs.Generative AI Integration: Work with AI models such as GPT, transformers, and other generative approaches to build advanced natural language generation, summarization, and conversational AI systems.Knowledge Graph Design: Design, implement, and maintain scalable knowledge graphs and semantic networks that capture structured and unstructured data for enhanced decision-making.Data Engineering: Collaborate with data scientists and engineers to prepare and process large datasets to train AI models and build knowledge graphs.Research & Innovation: Stay up-to-date with the latest advancements in AI, particularly in the areas of knowledge graphs, natural language understanding (NLU), and generative modeling. Apply cutting-edge research to improve product capabilities.Cross-Functional Collaboration: Work closely with product managers, researchers, and other engineers to translate business requirements into technical solutions.Performance Tuning & Optimization: Continuously improve the efficiency and accuracy of AI models and the knowledge graph infrastructure, ensuring minimal latency and high throughput.Documentation & Reporting: Maintain clear documentation of system architectures, model performance, and development processes to facilitate team collaboration and future updates.
Required QualificationsEducation:Bachelor’s or master’s degree in computer science, Engineering, or a related field.Experience:2+ years of hands-on experience in software development, particularly in Generative AI (e.g., GPT, BERT, transformer models, GANs).1+ years of experience working with Knowledge Graphs (e.g., GraphQL, RDF, OWL, SPARQL, Neo4j, or other graph databases).Solid understanding of Natural Language Processing (NLP) techniques and frameworks.Experience with cloud platforms (AWS, GCP, Azure) and deployment of AI systems.Skills:Strong proficiency in Python, Java, or C++ (with experience in TensorFlow, PyTorch, or similar AI/ML frameworks).Experience in building and optimizing Graph Databases and GraphQL APIs.Solid understanding of algorithms, data structures, and performance optimization techniques for large-scale AI systems.Familiarity with DevOps tools and CI/CD pipelines for deployment automation.Additional Skills:Strong analytical, problem-solving, and debugging skills.Ability to work in a collaborative and agile environment.Good communication skills, both written and verbal.Ability to translate complex technical concepts into clear business implications.
Preferred QualificationsExperience with Knowledge Representation or Ontology Management.Familiarity with AI Ethics and bias mitigation strategies in AI systems.Experience with Graph Neural Networks (GNNs) or other advanced graph-based AI techniques.Knowledge of semantic web technologies and linked data.