About the Job:
Kyndryl is seeking an accomplished MLOps Platform Architect to lead the design, build, and continuous operation of a cutting-edge Machine Learning Operations ecosystem. This individual contributor role is pivotal in creating scalable, secure, and performance-optimized platforms that integrate advanced AI and Agentic AI systems, enabling seamless deployment and management of machine learning models across both online and offline environments.
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Key Responsibilities:
- Architect, implement, and optimize end-to-end MLOps platforms supporting robust deployment pipelines for diverse ML workloads.
- Design scalable infrastructure for training, serving, and monitoring AI/ML models, leveraging parallel processing, load balancing, and performance tuning techniques.
- Develop and automate CI/CD pipelines incorporating Alpha/Beta testing and Blue/Green deployments, focusing on deployment automation and production readiness.
- Establish comprehensive model monitoring frameworks to track performance, detect drift, and ensure stability and compliance in production.
- Collaborate closely with data scientists, AI engineers, and platform teams to integrate AI models, support experimental workflows, and enhance platform usability.
- Ensure enterprise-grade platform security, governance, and operational compliance.
- Lead initiatives on platform scalability, cost efficiency, and resource provisioning, maintaining thorough architectural documentation.
- Proactively research and recommend cutting-edge technologies and best practices in MLOps to keep the platform at the forefront of innovation.
Required Qualifications:
- Bachelor’s or master’s degree in computer science, Engineering, Data Science, or related fields.
- Over 10 years of experience designing and operationalizing complex, scalable MLOps platforms with strong production readiness.
- Deep expertise in AI/ML lifecycle management, deployment automation, performance optimization, and scalable serving frameworks.
- Proficiency with advanced deployment strategies including Alpha/Beta testing, Blue/Green deployments, and load balancing.
- Hands-on experience in parallel processing techniques for scalable training and inference.
- Strong knowledge of modern data ecosystems, containerization (Docker, Kubernetes), orchestration, and cloud AI/ML services (AWS, Azure, GCP).
- Expertise in integrating AI engines and emerging Agentic AI technologies.
- Proven capability as a collaborative team player in cross-functional environments.
- Industry experience in enterprise AI/ML, preferably within financial services or regulated industries.
Preferred Qualifications:
- Skills in requirements gathering, translating business needs into technical platforms.
- Strong background in DevOps and infrastructure automation practices.
- Broad understanding of data science algorithms and AI model development.
- Advanced cloud architecture expertise and knowledge of data engineering platforms.
- Excellent communication, organizational, and documentation skills.
- Experience driving platform adoption, user experience improvements, and stakeholder engagement.
- Certifications in cloud platforms and MLOps tools are advantageous.
Language Requirements:
This role at Kyndryl offers an outstanding opportunity to architect and spearhead next-generation MLOps platforms that empower scalable, intelligent AI solutions for enterprise innovation and transformation. The ideal candidate thrives on technical excellence, strategic thinking, and impactful collaboration in a dynamic environment.
