Responsibilities:
- Design and develop scalable ML platforms and pipelines leveraging cloud and open-source technologies, and contribute to establishing coding standards and workflows
- Implement MLOps best practices for model serving, monitoring, and lifecycle management; and handle occasional on-call support and incident response for production ML systems
- Optimize ML workflows for scale, performance, and cost-efficiency; review and maintain existing tool-sets and codebases
- Collaborate with Data Science, Data Engineering, Product, and Marketing teams to create ML-driven decision-making data products
- Evaluate and adopt emerging ML technologies; contribute to the ML community and open-source projects
- Lead the design and deployment of ML model pipelines in collaboration with Data Science and Data Engineering teams
- Implement infrastructure-as-code, CI/CD, and automation for efficient ML operations
- Support the rollout of ML features, working closely with Product and Marketing teams
- Assist in defining and implementing ML governance policies
- Participate in scaling operations by developing automation scripts and reusable libraries
- Contribute to documenting best practices and creating technical documentation for ML systems
Position Requirements:
- 5+ years of experience building and deploying ML model pipelines at scale
- Expert-level knowledge of containerization, orchestration, and workflow management technologies (e.g., Kubernetes, Docker, Apache Airflow) for deploying and managing complex ML pipelines at scale
- Advanced Python skills, including expertise in ML-specific libraries and best practices
- Extensive experience with cloud-based ML platforms (e.g., AWS SageMaker, Azure ML, Google Cloud AI)
- Proven track record in implementing MLOps best practices, including CI/CD, automated testing, and code quality assurance
- Proficiency in ML frameworks (e.g., TensorFlow, PyTorch, Keras) and MLOps tools (e.g., MLflow, Kubeflow)
- Strong experience in cloud infrastructure management, including IaC, monitoring, and big data technologies
- Strong problem-solving skills and strong technical communication skills within the team
- Experience contributing to ML projects that deliver measurable business value in marketing or customer analytics