# AI / ML Engineer

**Company:** Accenture Greece
**Location:** Athens, Greece
**Workplace:** on site
**Employment type:** Full-time

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## Description

**YOU ARE  
**As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. Your role spans the full solution lifecycle — assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and DevOps & MLOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems.  
**THE WORK  
**-   Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions  
    
-   Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps & MLOps  
    
-   Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including edge device and HPC  
    
-   Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites  
    
-   Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production  
    
-   Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools  
    
-   Justify the value of model approaches in business problems  
    
-   Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production  
    
**EDUCATION  
**  
-   Bachelor's Degree or equivalent  
    
**Basic (required) Qualification  
**-   Proven experience as a machine learning engineer or scientist, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing.  
    
-   Minimum of 3 years of experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming  
    
-   Minimum of 1 years of experience in distributed computing systems and architecture that may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks  
    
-   Minimum of 1 years of experience in building and deploying AI/ML based software to a cloud environment.  
    
**Preferred Qualification  
**-   Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch)..  
    
-   Experience working with language models like LLM's APIs and optimizing their usage for specific applications.  
    
-   Experience with the following programming languages: Python, C++, Java, R, SQL  
    
-   Strong written & verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders  
    
-   Strong client-facing skillsets in a consulting environment  
    
-   Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams  
    
-   Entrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation  
    
-   MS or PhD in related field preferred (computer science, engineering, etc.)