Das ist der Job
Application Process
• Easy Apply on LinkedIn
• Participate in resume evaluation & interview stage
Darum lohnt es sich
Requirements
• Proven expertise in machine learning algorithms, model development, and deployment.
• Strong programming skills, ideally in Python or Java, with experience in large-scale software engineering projects.
• In-depth experience with CI/CD workflows and automation tools.
• Hands-on expertise with AWS cloud services for ML applications and data pipelines.
• Advanced knowledge of Kubernetes for orchestrating containerized ML workloads.
• Exceptional written and verbal communication skills, with a focus on clear technical documentation and team collaboration.
• Demonstrated ability to scope, structure, and solve complex, real-world data challenges. • Design, build, and optimize robust machine learning models for production environments.
• Implement and automate end-to-end ML pipelines using CI/CD best practices.
• Leverage AWS services for scalable AI infrastructure and model deployment.
• Orchestrate containerized workloads using Kubernetes to ensure high availability and seamless scalability.
• Collaborate with data scientists, engineers, and researchers to translate complex business problems into actionable ML solutions.
• Evaluate, preprocess, and frame real-world data problems for effective machine learning applications.
• Document and communicate findings, solution approaches, and technical decisions with clarity and precision.
