Related skills
docker aws sql python kubernetes📋 Description
- Design, build, and maintain scalable ML infra on AWS (SageMaker).
- Develop ML solutions for recommendations, fraud, and credit risk.
- Lead MLOps to automate training, testing, and deployment.
- Collaborate with product teams on MVP AI features.
- Provide production support; on-call troubleshooting for ML.
- Scale ML architecture for rapid user growth on AWS.
🎯 Requirements
- 6+ years ML eng exp deploying scalable models.
- BS in CS/Math/EE or related field, or equivalent.
- Python proficiency; Golang a plus.
- Strong AWS and SageMaker ML deployment experience.
- Kubernetes, Docker, and CI/CD for ML.
- SQL, data warehouses; relational DBs.
- Monitoring tools: Prometheus, Grafana, CloudWatch.
🎁 Benefits
- Remote-friendly, full-time role (#Li-remote).
- Collaborative, high-performance culture.
- Work with cutting-edge ML and Generative AI.
- Career growth in fintech and retail tech.
Meet JobCopilot: Your Personal AI Job Hunter
Automatically Apply to Engineering Jobs. Just set your
preferences and Job Copilot will do the rest — finding, filtering, and applying while you focus on what matters.
Help us maintain the quality of jobs posted on Empllo!
Is this position not a remote job?
Let us know!