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Moderate due to popular ML/AI role, broad skillset, and global employer presence.
Medium because ML/AI expertise plus cloud engineering is transferable but requires domain-specific machine learning experience.
High due to broad mandatory cloud, ML, microservices, and containerization skill requirements.
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Design, develop, and test software systems and micro-services with ML/AI algorithm integration on telemetry and structured/unstructured data.
Accountable for writing, testing, refactoring code, automated testing, deployment, and cross-team code reviews.
Collaborate with product teams and contribute to large scale distributed systems, API development, and solution automation.
Bachelor's degree or equivalent in Computer Science, Engineering or related field.
Seasoned software development experience, including micro-services, RESTful APIs, and working with large data sets using ML/AI algorithms.
Strong proficiency in multiple programming languages such as C/C++, C#, Java, JavaScript, Python, Node.js.
Work Experience Required: Seasoned experience with geo-distributed teams, Agile/Lean methodologies, full software delivery lifecycle tools, and cloud architecture across public clouds (AWS, Azure, GCP).
Deep expertise in cloud architecture, container runtimes (Kubernetes, Docker), and CI/CD pipelines.
Experienced in developing micro-services and API products with strong software design, data structure, algorithm, and debugging skills.
Proven ability to work across global teams through all software development phases maintaining high quality and performance.