About the Job:
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like. You will be supported and inspired by a collaborative community of colleagues around the world, and you’ll have the opportunity to reimagine what’s possible. Join us in helping the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
Responsibilities:
- Collaborate with cross-functional teams to define research methodologies and AI product requirements.
- Ensure model scalability, performance, and integration into healthcare workflows.
- Oversee the data pipeline architecture, from data collection to model deployment.
- Lead data science delivery pod, ensuring best practices in model development and experimentation.
- Socialize findings and actionable insights with stakeholders, including healthcare professionals and decision-makers.
Skills Required:
- Expertise in machine learning (NLP, Deep Learning, CV, Generative AI, etc.) and healthcare data sources.
- Proficiency in SQL, Python, Spark, and ML libraries (TensorFlow, PyTorch, Spark MLlib, MLFlow, LangChain, LlamaIndex, etc.).
- Well-versed in MLOps and LLMOps architectures.
- Experience working with developer tools such as Azure DevOps, PyCharm/MS Visual Studio, Docker, etc.
- Experience with Databricks and cloud platforms (preferably Azure).
Why You Should Consider Capgemini:
Capgemini is dedicated to growing clients’ businesses while building a more sustainable and inclusive future. When you join Capgemini, you’ll become part of a diverse collective of thinkers and industry experts, seeking innovative ways technology can transform the world's leading businesses. You’ll gain valuable experiences and connections to shape your future, while using your skills to help clients leverage technology to innovate and grow their businesses.
Language Requirements:
Not specified in the job listing.
