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SeniorFull-timePythonAWSGCPKubernetesDockerMachine LearningData ScienceTensorFlowPyTorchCI/CD
Salary Range
$143,650 - $194,350 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
ClickUp is seeking a technical expert in recommendation systems and advanced deep learning to architect comprehensive machine learning pipelines and deployment strategies. This role involves building Next Best Offer systems and integrating scalable machine learning architectures into customer-facing applications.
Key Responsibilities
- →Build advanced recommendation models, such as Next Best Offer systems, leveraging cutting-edge techniques
- →Create and own the end-to-end lifecycle of machine learning models, from data preprocessing to production deployment
- →Design and deploy scalable machine learning architectures that integrate seamlessly into customer-facing applications
- →Continuously evaluate and improve model accuracy, scalability, and computational efficiency
- →Stay up-to-date with the latest advancements in machine learning to ensure best-in-class solutions
- →Collaborate with cross-functional partners in Product, Engineering, Analytics, and Marketing
- →Identify new opportunities to uncover actionable insights from large-scale datasets
- →Grow the effectiveness of the PLG funnel through optimized model performance and personalization
Requirements
- ✓5+ years of direct experience in data science or machine learning, with a specific focus on recommendation systems
- ✓Proven experience deploying machine learning models end-to-end in a SaaS or PLG environment
- ✓Strong proficiency in Python and deep learning frameworks such as TensorFlow or PyTorch
- ✓Hands-on experience with GNN, Transformers, or other advanced ML architectures
- ✓Solid understanding of MLOps best practices, data pipelines, and containerization (Docker, Kubernetes)
- ✓Expertise in working with large-scale datasets and distributed computing tools (e.g., Spark, Hadoop)
- ✓Strong problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders
- ✓Hands-on experience with the modern data stack: Snowflake, Hex, and cloud platforms (AWS/GCP)
- ✓Solid understanding of MLOps best practices and CI/CD for machine learning (MLflow, Docker, Kubernetes)
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