ML Architect

Title: Machine Learning ArchitectLocation: San Jose, CA (Hybrid)Long Term Contract On C2CJob SummaryWe are seeking an experienced Machine Learning Architect to design, develop, and oversee scalable AI/ML solutions that support business objectives. The ML Architect will lead the architecture of machine learning systems, define technical standards, collaborate with data scientists and engineers, and ensure production-ready deployment of AI models.Key ResponsibilitiesDesign end-to-end machine learning and AI architectures for enterprise applications.Define standards, frameworks, and best practices for model development, deployment, monitoring, and governance.Collaborate with data scientists, data engineers, software engineers, and business stakeholders.Evaluate and select appropriate ML algorithms, tools, cloud services, and infrastructure.Architect MLOps pipelines for continuous integration, deployment, monitoring, and retraining.Ensure scalability, security, reliability, and performance of ML platforms.Guide model lifecycle management, including experimentation, validation, deployment, and maintenance.Lead technical reviews and provide architectural guidance to development teams.Stay current with advancements in AI, machine learning, deep learning, and generative AI technologies.Support regulatory compliance, data privacy, and AI governance requirements.Required QualificationsBachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field.8+ years of experience in software engineering, data science, or machine learning.3+ years of experience designing enterprise-scale ML architectures.Strong knowledge of machine learning, deep learning, and statistical modeling techniques.Proficiency in Python and ML frameworks such as:TensorFlowPyTorchScikit-learnExperience with cloud platforms:Amazon Web Services (AWS)Microsoft AzureGoogle Cloud PlatformExperience with containerization and orchestration tools:DockerKubernetesStrong understanding of MLOps, CI/CD, data engineering, and distributed computing.Preferred QualificationsExperience with Generative AI and Large Language Models (LLMs).Knowledge of vector databases, retrieval systems, and AI agents.Experience with model governance, explainability, and responsible AI practices.Relevant cloud or AI certifications.