Sr ML Platform Engineer 20762

• Evaluate and select appropriate cloud services for each stage of the ML lifecycle.
• Design and implement the overall architecture of the MLOps platform.
• Set up automated pipelines for data preparation model training and deployment.
• Implement version control for code data and models to maintain reproducibility and traceability.
• Ensure the platform is scalable secure and compliant with relevant regulations.
• Provide tools and interfaces for data scientists to easily leverage the platform.
• Continuously optimize the platform for performance and costefficiency.
• Develop tools and interfaces for data scientists to easily utilize the platform s capabilities.
• Bridge the gap between data science and operations enabling efficient development deployment and maintenance of ML models at scale.

• Bachelor s/Master s degree in Engineering Computer Science or equivalent experience.
• At least 10 years of professional experience in building cloudbased applications including ML platforms.
• Extensive expertise in cloud platforms like AWS Google Cloud Platform or Azure (Azure preferred).
• Proficiency in DevOps practices including CI/CD pipelines containerization (Docker Kubernetes) and infrastructure as code.
• Strong understanding of ML workflows model training deployment processes and data engineering pipelines.
• Advanced programming skills particularly in Python with a focus on ML applications.
• Experience in designing secure scalable systems that adhere to regulatory compliance.
• Demonstrated ability to collaborate with crossfunctional teams including data scientists and software engineers.

test case development,reinforcement learning,business sense,random forest,keras,agile software development practices,solution refinement,code-creation technologies,mandarin,software quality assurance,problem-solving,communication,opencv,software development best practices,ai-driven solutions,ai systems,data engineering pipelines,communication skills,css3,infrastructure as code,conflict resolution,resource management,scikit-learn,large language models (llms),github,c/c++ programming,algorithmic problems,redux,written communication skills,c,computer vision,cloud platforms,rnns,jupyter notebooks,mentorship,cross-functional collaboration,code review,salesforce development,tool customization,spoken communication skills,component-driven architecture,engineering,software development,mlops,ci/cd pipelines,deep learning models,code design,tikz,ai technology,automation,git,pytorch,cnns,pgf,test planning,code reviews,react js,analytical abilities,javascript,leadership,html5,numpy,image processing,apex,salesforce apis,stakeholder engagement,responsive design,c++,integration patterns,web performance optimization,quality control,english communication,gans,python,mobile coding domain,transfer learning,containerization,lightning components (aura),svg,version control systems,strong communication skills,tensorflow,devops practices,d3.js,cross-browser compatibility,strategic thinking,svm,data analysis,lwc,python programming,data integrity,critical thinking,code,machine learning workflows,pandas,decision trees,visualforce pages,typescript,backend development,solution debugging,machine learning,k-nn