ClickUp
Growth Machine Learning Engineer
Kentucky, USA · full-time
No sponsorship$150k-$185kDetected 55 days ago
PythonAlgorithmsSQLAWSGCPAzureCloud PlatformsDockerKubernetesCI/CDMachine LearningTensorFlowPyTorchscikit-learnSparkData EngineeringData ScienceMLOpsRecruitingResearchCommunicationCollaborationProblem SolvingHadoop
About the role
- Model Development & Deployment: Deploy production-grade machine learning models, ensuring reliability, low latency, and scalability.
- Model Performance & Monitoring: Establish monitoring frameworks to track model performance, detect drift, and trigger retraining as needed.
- Collaboration: Act as a bridge between data science and software engineering teams, ensuring seamless integration of ML models into broader product and platform architectures.
Responsibilities
- You will collaborate closely with data scientists, analysts, and data engineering teams to build robust, scalable ML systems that drive impactful business decisions.
- Build and maintain end-to-end ML pipelines, including automated training, evaluation, versioning, deployment, and monitoring workflows.
- Partner with data scientists to design, implement, and optimize feature pipelines that feed into ML models, ensuring data quality and freshness.
- MLOps & Infrastructure: Build and maintain end-to-end ML pipelines, including automated training, evaluation, versioning, deployment, and monitoring workflows.
- Feature Engineering: Partner with data scientists to design, implement, and optimize feature pipelines that feed into ML models, ensuring data quality and freshness.
Skills
- Strong proficiency in Python and experience with ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Hands-on experience with MLOps tools and platforms (e.g., MLflow, SageMaker, Kubeflow, Vertex AI).
- Solid SQL skills and experience with data warehouses and feature stores.
- Experience with big data technologies (e.g., Spark, Hadoop) and streaming frameworks.
- Expertise in cloud platforms (e.g., AWS, Google Cloud Platform, Azure) and containerization tools (e.g., Docker, Kubernetes).
- Familiarity with CI/CD practices applied to ML workflows.
- Desirable Education: Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, Engineering, or a related field.
Compensation
- $150k-$185k
Benefits
- This role sits at the intersection of machine learning, data science, and MLOps, requiring you to own the full lifecycle of ML systems - from feature engineering to model production deployment and monitoring.
Company info
- At ClickUp, we're not just building software.
- Join us and be part of a bold, innovative team that's redefining what's possible!
- We are seeking a highly skilled and motivated ML Engineer to join our team.
Equal opportunity
- Employer ClickUp is an Equal Opportunity Employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.
- If you have questions or need an accommodation in the recruitment process, please contact us at
Visa & Work Authorization
- Please note we are unable to sponsor or take over sponsorship of an employment visa for roles outside of engineering and product at this time.
- Sponsorship for engineering and product roles is not guaranteed, but is instead based on the business needs for that specific role at that time.
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This listing is sourced directly from ClickUp's careers page and normalized into a canonical job model.