Posted Apr 7, 2026
Key Responsibilities:
Model Development and Maintenance: Design, develop, test, deploy, and retrain machine learning models and algorithms in collaboration with data scientists and engineers. - Data Processing: Implement big data processing workflows and pipelines to handle large-scale datasets efficiently. - MLOps & LLMOps: Promote and implement MLOps and LLMOps best practices for model deployment, monitoring, and maintenance. - Platform Management: Maintain and enhance data science and machine learning platforms to ensure high performance and reliability. - Collaboration: Work closely with business stakeholders to understand their needs, provide insights, and deliver tailored ML solutions. - Security & Cost Management: Ensure all systems and solutions are secure and cost-effective. Qualification Required:
Educational Background: Bachelors or Masters degree in Computer Science, Data Science, Machine Learning, or related field preferred. - Experience: 5 years of proven experience in machine learning model development, deployment, and maintenance. Some experience with large language models is a plus. - Technical Skills: Proficiency in Python, R, or similar programming languages. Experience with ML frameworks like TensorFlow, PyTorch, or Scikit-learn. - Big Data Technologies: Familiarity with big data processing tools, especially Spark, or similar. - MLOps & LLMOps: Knowledge of MLOps and LLMOps practices and tools such as Docker, Kubernetes, MLflow, etc. - Palantir Foundry: Willingness to accustom yourself with Swiss Re's strategic data management platform Palantir Foundry. Prior experience with the platform is a plus. - Analytical Skills: Strong analytical and problem-solving skills with the ability to work with complex datasets. - Communication: Excellent communication skills to interact effectively with both technical and non-technical stakeholders. Key Responsibilities:
Model Development and Maintenance: Design, develop, test, deploy, and retrain machine learning models and algorithms in collaboration with data scientists and engineers. - Data Processing: Implement big data processing workflows and pipelines to handle large-scale datasets efficiently. - MLOps & LLMOps: Promote and implement MLOps and LLMOps best practices for model deployment, monitoring, and maintenance. - Platform Management: Maintain and enhance data science and machine learning platforms to ensure high performance and reliability. - Collaboration: Work closely with business stakeholders to understand their needs, provide insights, and deliver tailored ML solutions. - Security & Cost Management: Ensure all systems and solutions are secure and cost-effective. Qualification Required:
Educational Background: Bachelors or Masters degree in Computer Science, Data Science, Machine Learning, or related field preferred. - Experience: 5 years of proven experience in machine learning model development, deployment, and maintenance. Some experience with large language models is a plus. - Technical Skills: Proficiency in Python, R, or similar programming languages. Experience
Don't want to apply yourself?
Our team writes your resume, applies for you, preps you for interviews, and negotiates your offer.
Browse Jobs
By Role
By City