AI/ML Computational Scientist Manager (All Genders) at Accenture

Accenture; Kronberg im Taunus; Vor Ort; EUR 90.000 - 120.000; Vollzeit

Zusammenfassung

Accenture in Kronberg im Taunus, Germany, is seeking an AI/ML Computational Scientist for a full-time on-site role. You will design, build, and operationalize AI/ML solutions for enterprise clients, integrating custom models with cloud and third‑party AI services to deliver production‑ready outcomes.

You will work across the full lifecycle—from problem framing and data assessment to model customization (including Deep Learning, Gen AI, and LLMs) and scalable MLOps pipelines, ensuring

Qualifikationen

• Proven experience as a machine learning engineer or scientist, deploying models in production at scale, including monitoring, alerting, and auditing.
• Strong foundations in computer science, distributed computing, and data processing for model training and production.
• Experience with Deep Learning, Gen AI, and large language models and applying them to real-world business problems.

Aufgaben

• Formulate real-world problems into scalable AI/ML solutions.
• Develop and implement machine learning algorithms and models.
• Design and build scalable data pipelines to support training and production with DevOps & MLOps.
• Customize and apply Deep Learning and Gen AI models for various use cases.
• Engage in R&D of new AI and HPC algorithms for client applications.
• Work with large-scale datasets and preprocess data for training.

Kenntnisse

Python

TensorFlow

PyTorch

LLMs APIs

Java

C++

SQL

DevOps

MLOps

Data pipelines

Cloud computing

Edge computing

Ausbildung

Bachelor's Degree

Tools

HPC

Cloud platforms

Jobbeschreibung

Kronberg, HE, DE. This Full time on site position offers great opportunities for career growth.

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

Proven experience as a machine learning engineer or scientist, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing. Considerable 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.)