North AmericaFull TimeEngineering
Remotely
machine learningcloudllmmlopsobservabilitypipelinesci/cd
Job Description
📋 Description
- Design and implement scalable ML/LLM pipelines across use cases.
- Build production-grade ML/LLM infrastructure.
- Develop modular components and CI/CD for rapid experimentation.
- Establish standards for scalability, reliability, security, testing, compliance.
- Implement observability, drift detection, logging, and rollback strategies.
- Deploy ML solutions using cloud platforms and cloud data services.
🎯 Requirements
- 8+ years of professional ML engineering experience.
- At least 2 years working with large language models and LLM apps.
- Strong skills in scalable ML pipelines for traditional ML and LLM workloads.
- Experience automating, deploying, monitoring, and maintaining ML workflows in production.
- Hands-on with cloud platforms, including deployment, resource management, and APIs for data.
- Strong production ML engineering practices: reliability, observability, testing, CI/CD, and
🎁 Benefits
- Annual cash compensation of $210,000–$250,000.
- Stock options as part of total compensation.
- Comprehensive employee benefits and perks.
- Opportunity to work on advanced AI/ML challenges with real-world impact.
- Exposure to complex LLM/ML systems in an AI-native environment.
- Strong leadership, mentorship, and professional growth opportunities.