![Capgemini](https://contents.bebee.com/companies/se/capgemini/avatar-ZVwUb.png)
Machine Learning Engineering Manager
12 hours ago
**Job Summary:**
Capgemini is seeking an experienced AI/ML Architect to join our team. As an AI/ML Architect, you will be responsible for designing and implementing AI and machine learning solutions that meet business requirements and technical specifications.
Your Responsibilities Will Include:
- Designing and architecting end-to-end AI/ML solutions.
- Developing and implementing scalable machine learning and deep learning models.
- Creating architectures for NLP applications, including text processing, sentiment analysis, named entity recognition, and language modelling.
- Leveraging generative AI and large language models (LLMs) to develop innovative applications.
- Collaborating with data engineers to design data pipelines and ensure data quality and accessibility.
- Providing technical leadership and guidance to data scientists and engineers throughout the development lifecycle.
- Evaluating and selecting appropriate AI/ML tools, frameworks, and technologies to meet project needs.
- Ensuring best practices in AI/ML model development, including versioning, testing, and validation.
- Staying updated with the latest advancements in AI/ML technologies and incorporating them into architectural designs.
- Communicating complex AI/ML concepts and solutions effectively to non-technical stakeholders.
About Us:
Capgemini is a global leader in consulting, technology services, and digital transformation. We help our clients achieve their goals by providing innovative solutions to complex problems.
What We're Looking For:
- A highly skilled AI/ML Architect with a strong background in designing and implementing AI and machine learning solutions.
- Excellent communication and leadership skills, with the ability to guide cross-functional teams.
- Experience working with machine learning algorithms, model development, and deployment.
- Proficiency in deep learning frameworks such as TensorFlow, PyTorch, and Keras.
- Strong expertise in NLP techniques and tools, including experience with LLMs like Gemini, GPT, BERT, etc.
- Experience with cloud platforms (AWS, GCP, Azure) and their AI/ML services.
- Knowledge of big data technologies and tools such as Hadoop, Spark, and Kafka.
- Proficiency in programming languages such as Python, R, and Java.
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