Deep AI native software engineer

ph3YOU ARE /h3 pAs 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. /p h3THE WORK /h3 ul liFormulate real‑world problems into practical, efficient, and scalable AI and Machine Learning solutions /li liDevelop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps MLOps /li liCustomize 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 /li liEngage 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 /li liWork with large‑scale datasets and utilize data preprocessing techniques to ensure high‑quality input for training and production /li liImplement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools /li liJustify the value of model approaches in business problems /li liCollaborate 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 /li /ul h3EDUCATION /h3 ul liBachelor's Degree or equivalent /li /ul h3Basic Qualifications /h3 ul liProven experience as a machine learning engineer or scientist, deploying models in production at scale, including monitoring, alerting, automatic bug filing, and auditing /li liExperience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming /li liHands‑on 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 /li liExperience in building and deploying AI/ML based software to a cloud environment /li /ul h3Preferred Qualifications /h3 ul liProficiency in Python and python‑based AI/ML frameworks and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch) /li liExperience working with language models like LLM APIs and optimizing their usage for specific applications /li liExperience with the following programming languages: Python, C++, Java, R, SQL /li liStrong written verbal communication skills and ability to communicate complex technical concepts to non‑technical stakeholders /li liStrong client‑facing skillsets in a consulting environment /li liStrong cross‑functional skills with the ability to collaborate with a variety of internal and client‑side teams /li liEntrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation /li liMS or PhD in related field preferred (computer science, engineering, etc.) /li /ul h3Compensation /h3 pCompensation at Accenture varies depending on a wide array of factors including but not limited to role, level, seniority, responsibility, skillset, and level of experience. For this position, the Metalmeccanico National Collective Bargaining Agreement applies, with one of the following pay grades and corresponding gross annual salary range: B2 €32,000 - €50,500; B3 €36,000 - €65,800. /p /p #J-18808-Ljbffr