Data Science Solutions Designer

10 hours ago


Stockholm, Stockholm, Sweden Capgemini Full time
Job Details:

As an AI Solutions Architect at Capgemini Group IT, you will be responsible for designing and architecting AI/ML solutions that meet business requirements and technical specifications. You will work closely with data scientists, engineers, and business stakeholders to ensure that our AI/ML initiatives are scalable, robust, and aligned with business objectives.

Key Responsibilities:

  1. Design and Development: Design and develop end-to-end AI/ML solutions that meet business requirements and technical specifications.
  2. Machine Learning Model Development: Create scalable machine learning and deep learning models, ensuring they integrate seamlessly into existing systems.
  3. NLP Application Architecture: Design architectures for NLP applications, including text processing, sentiment analysis, named entity recognition, and language modeling.
  4. Generative AI and LLMs: Leverage generative AI and large language models (LLMs) to develop innovative applications.
  5. Collaboration and Communication: Work with data engineers to design data pipelines and ensure data quality and accessibility, and effectively communicate complex AI/ML concepts and solutions to non-technical stakeholders.

Requirements and Qualifications:

  1. Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
  2. 8+ years of experience in designing and implementing AI/ML solutions, with a strong focus on machine learning, deep learning, NLP, and generative AI.
  3. Extensive experience with machine learning algorithms, model development, and deployment.
  4. Proficiency in deep learning frameworks such as TensorFlow, PyTorch, and Keras.
  5. Strong expertise in NLP techniques and tools, including experience with LLMs like Gemini, GPT, BERT, etc.
  6. Experience with cloud platforms (AWS, GCP, Azure) and their AI/ML services.
  7. Knowledge of big data technologies and tools such as Hadoop, Spark, and Kafka.
  8. Proficiency in programming languages such as Python, R, and Java.
  9. Excellent problem-solving skills and the ability to design robust, scalable AI/ML architectures.
  10. Strong communication skills, with the ability to present technical concepts to both technical and non-technical audiences.
  11. Experience in leading and mentoring technical teams.


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