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Technical Architect, AI & MLOps - Chicago Illinois
Company: Echo Global Logistics
Location: Chicago, Illinois
Posted On: 01/21/2025
As an Technical Architect with a focus on Artificial Intelligence and MLOps, you will lead the architecture, design, and integration of AI-driven solutions across the enterprise. This role requires extensive experience in architecting data science platforms, MLOps pipelines, and designing data structures for large-scale AI models. You will collaborate with business and technical teams to address complex challenges, drive the adoption of AI technologies, and ensure scalable, high-performance solutions that align with business goalsJob Duties & Responsibilities - Architect and design AI, Data Science, and MLOps solutions that scale across the enterprise, supporting both experimentation and production environments.
- Develop a deep understanding of business needs and technical roadmaps to architect cross-functional solutions for data science initiatives.
- Design data structures and databases that effectively support machine learning models, AI workloads, and data-driven applications.
- Lead efforts to build and optimize MLOps pipelines to enable seamless model development, testing, deployment, and monitoring across the enterprise.
- Decompose AI/ML challenges into technical components such as data ingestion pipelines, feature stores, model repositories, and API endpoints, and produce detailed architectural documentation.
- Collaborate with data scientists, engineers, and DevOps teams to ensure smooth integration of AI models into business applications.
- Provide technical leadership in the evaluation and selection of AI platforms, tools, and frameworks for model training, versioning, and lifecycle management.
- Ensure solutions adhere to enterprise architecture standards, including security, scalability, performance, and compliance requirements.
- Identify and mitigate architectural risks related to AI/ML solutions, including issues related to data integrity, model performance, and operationalization challenges.
- Lead knowledge-sharing sessions to align stakeholders on technical architectures and solutions.
- Continuously evaluate emerging technologies and trends in AI, machine learning, and data science, incorporating these into the organization's technology roadmap.Required Skills
- BA or BS, preferably in Computer Science, Engineering, Data Science, or related discipline, or equivalent work experience.
- 10+ years of hands-on experience in the design and implementation of complex, high-volume software systems, with at least 5+ years focusing on AI/ML architecture, data science solutions, and MLOps.
- Expertise in data architecture, including designing and optimizing data structures for large-scale machine learning models and AI applications.
- Extensive experience with MLOps frameworks (e.g., Kubeflow, MLflow, Seldon) and cloud-based data science platforms (AWS Sagemaker, Google AI, or Azure AI).
- Proven experience in building end-to-end AI/ML solutions - from data pipelines to model deployment and monitoring.
- Strong knowledge of machine learning algorithms model lifecycle management, and model deployment best practices.
- Expertise in cloud architectures (AWS, Azure, GCP), containerization (Docker, Kubernetes), and CI/CD pipelines.
- Experience in designing and developing event-driven architectures* microservices, and API-based integrations.
- Solid understanding of enterprise security best practices for AI, including secure model access, data privacy, and compliance.
- Experience with relational and NoSQL databases to support AI/ML data storage and retrieval.
- Leadership experience mentoring and guiding technical teams in AI, MLOps, and data science.Preferred Skills
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