Job Description
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.
YOU ARE
Responsible for delivering real‑world AI solutions that are practical, efficient, and scalable, while collaborating closely with business and technical stakeholders to achieve end‑to‑end project goals.
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 Generative AI models for various use cases based on business needs, data availability, system and infrastructure requirements — including edge devices 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.
Qualification
EducationBachelor’s Degree in Computer Science, Computer Engineering, Data Science, or a related field.
BASIC (REQUIRED) QUALIFICATIONWork or coursework experience with machine learning engineering or machine learning science, deploying models in production at scale, including monitoring, alerting, automatic bug filing, and auditing.
Experience (work or coursework) in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming.
PREFERRED QUALIFICATIONProficiency in Python and Python‑based AI/ML frameworks and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch).
Experience working with language models like LLM 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 curiosity and passion for emergent tech and driving innovation.
Locations
- London
- Berlin
- Madrid
- Paris
Equal Employment Opportunity Statement
All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process.Accenture is committed to providing veteran employment opportunities to our service men and women.Please read Accenture’s Recruiting and Hiring Statement for more information on how we process your data during the Recruiting and Hiring process.
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