Principal MLOps Engineer; Remote

Position: Principal MLOps Engineer (Remote) The Principal MLOps Engineer in the Acxiom Data Science and Machine Learning team will spearhead the development of an MLOps platform to support the development and lifecycle of Acxiom’s modeled propensities. This role integrates software engineering, AI/ML engineering, data proficiency, and MLOps experience to build a state-of-the-art MLOps solution that can power our model product builds, and other complex marketing activities. As a Principal MLOps Engineer, you will collaborate with the MLOps engineering lead to modernize and operationalize Acxiom's Machine Learning platform and its machine learning pipelines, which process terabytes of data. Your responsibilities include defining requirements, partnering with the Architecture Center of Excellence to establish the new MLOps platform architecture, and leading the hands‑on development of MLOps pipelines capable of supporting a large portfolio of ML models and their life cycles. This role can be located almost anywhere in the U.S. What You Will Do: • Partner with the MLOps Engineering leader, Architecture and data science teams to design and develop hyperscale ML engineering and MLOps solutions and pipelines. • Partner with resources across US, Europe and Asia to own development and modernization activities • Assess current state of MLOps and AI/ML/GenAI capabilities, identify gaps, and design target‑state architectures to support ongoing modeled product builds, innovation, revenue growth, and operational excellence. • Own the development of new modernized MLOps infrastructure and migration of existing data products to new infrastructure • Develop automated AI and ML workflows and end‑to‑end pipelines for data preparation, training, deployment, and monitoring, ensuring the quality of architecture and design of our ML systems and data infrastructure. • Collaborate with Data Scientists, Product Owners, ML Engineers, and Software Engineers to design and deliver ML solutions, promote models and associated MLOps pipelines into production. • Leverage AI to develop GenAI‑powered solutions to complement our data science and product build capabilities. • Lead transformational initiatives to bridge the gap between current and desired AI/ML capabilities, collaborating with cross‑functional teams to ensure successful implementation. • Establish governance frameworks and decision criteria for AI/ML and GenAI projects, ensuring adherence to industry standards, regulatory requirements, Responsible AI principles, and Acxiom/IPG’s architectural guidelines. • Partner with Architecture COE to create and maintain reference architectures, patterns, and best practices for the AI/ML lifecycle and its integration within Acxiom’s enterprise ecosystem. • Own the ongoing support of this modernized platform once its built and operationalized developing new features and capabilities. • Lead the ongoing technology evaluation and process improvements to drive experimentation, model development, and MLOps at scale. • Lead and drive standardization of LLM onboarding processes, RAG pipelines, and application development. • Conduct periodic architecture reviews and risk assessments for proposed AI/ML solutions, ensuring they meet security, scalability, and interoperability requirements. • Maintain high reliability of machine learning pipelines in production environments, ensuring minimal downtime and optimal performance. What You Will Have: • 10+ years of experience in enterprise architecture, with a focus on AI/ML integration and transformation projects. • 8+ years of professional experience in software development. • Bachelor’s Degree in Computer Science or Associate Degree & 8+ years of development experience or equivalent experience. • Strong computer science fundamentals in object‑oriented design, data structures, algorithm design, problem‑solving, and complexity analysis. • Proficiency in at least two modern programming languages such as Java, C++, C, or Python. Preferred Skills: • 10+ years of experience in MLOps and ML Platform engineering, especially architecting scalable MLOps infrastructure and big data systems. • Proven experience building ML platforms that can run large‑scale model training & inferences (Trillions of inferences). • Prov… Apply tot his job