Machine Learning Architect

Tiger Analytics is looking for an experienced Machine Learning Architect to join their fast-growing advanced analytics consulting firm. The ideal candidate will have over 10 years of experience in data science, machine learning, and MLOps, and a deep understanding of scalable system design, model lifecycle management, and production-grade deployment pipelines.

Requirements

• Design and define system architecture for ML and AI-driven solutions across multiple business verticals.
• Lead ML system design discussions and make high-level design choices for model serving, data pipelines, and MLOps frameworks.
• Architect scalable and secure cloud-native platforms for ML model training, validation, deployment, and monitoring (AWS/GCP/Azure).
• Build reusable components and reference architectures for various stages of the ML lifecycle.
• Define and enforce best practices in model versioning, CI/CD for ML, testing, and rollback strategies.
• Deploy and manage machine learning & data pipelines in production environments.
• Work on containerization and orchestration solutions for model deployment.
• Participate in fast iteration cycles, adapting to evolving project requirements.
• Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
• Collaborate with Data scientists, software engineers, data engineers, and other stakeholders to develop and implement best practices for MLOps, including CI/CD pipelines, version control, model versioning, monitoring, alerting and automated model deployment.
• Ability to work with a global team, playing a key role in communicating problem context to the remote teams
• Excellent communication and teamwork skills

Benefits

• This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.