AI/ML Computational Science Manager

Accenture UK & Ireland

ML EngineermidLondon, England, UKonsitefulltimeIT Services and IT ConsultingMachine LearningDeep LearningGenerative AILarge Language ModelsMLOpsPythonTensorFlowPyTorchposted 21 Jul
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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 MLOps/LLMOps 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 - Experience as a machine learning engineer or scientist, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing. - Experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming - 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 - 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.)