Generative AI Engineer

In Accenture Technology, we investigate and explore new technologies to determine how our clients can use them – helping their business innovate, grow and improve.If you are a software engineer with experience dealing with data and putting AI&ML applications in production, we invite you to join the fast-growing Accenture Data Science & Machine Learning Engineering practice in Europe and work as part of a worldwide team of experts. In this position you should be able to build and deliver end-to-end solutions with focus on data science and machine learning components.Different technologies that you will be able to work with:Python, RPyTorch, Keras, Tensorflow, SciKit, MLlib,Azure ML, AWS SageMaker, GCPHadoop, Beam, DatabricksDocker, KubernetesStatistics, Probabilities,LLMs, Diffusion ModelsGenerative AIOur future colleague will do:Convert data science experiments into deployable web services, ensuring high availability and scalabilityShip in-house and off-the-shelf machine learning models, including LLMs and Diffusion modelsDesign and implement appropriate data models and flows to meet project requirements (ETL, Embedding Models, Vector Databases, etc.)Orchestrate the deployment of on-premise or cloud-based solutionsCreate and manage RESTful APIs to manage inference, monitoring and retraining of modelsBe involved in various stages of analytics/DS&ML projects, from data gathering to MLOps;JOb Requirements: What will help you succeed:3+ years of experience in Software engineering1+ years of experience in Data Science and Machine LearningExperience using one or more scripting or programming languages like Python, C#, or similar.Proficient with Linux, Docker, distributed computing and similarity search techniquesFamiliar with data visualization tools like PowerBI, Plotly or similarFamiliar with machine learning and deep learning models.Familiar with Large Language Models (LLM) and Diffusion Models (e.g., Stable Diffusion)Experience with processing/modeling big dataExperience on cloud technologies like Azure ML/AWS SageMaker or similar.Familiar with MLOps approach and methodologyReasons for being our colleague:Flexible working arrangements (Flex-work, Home Office)Option to participate on projects abroadContinuous growth in a positive and multicultural work environmentWide range of leading-edge trainings (including language course)Access to trainings, materials and bootcamps to build/enhance your skillsFamily oriented benefitsShare purchase planTransparent bonus structureRefer-a-Friend – get a bonus in the employee referral program!