**Principal ML / MLOps Engineer (open to relocation)
Location:**
Atlanta, GA (Hybrid)
Experience:
7–10+ years
Level:
Principal / Staff (Individual Contributor)
About the Role:
We’re hiring a Principal ML / MLOps Engineer to d
esign and deploy production-grade machine learning systems that support core business use cases such as pricing, forecasting, optimization, and supply chain.
This is a hands-on individual contributor role with senior scope and influence, not a people manager position. You’ll lead technical strategy, own ML systems end-to-end, and partner closely with engineering and business teams to move models from POC to production at scale.
What You’ll Do:
- Build, deploy, and operate ML systems in production (modeling, pipelines, monitoring, retraining).
- Lead technical direction for ML initiatives without formal people management.
- Work directly with product and commercial teams to translate business problems into ML solutions.
- Design cloud-native ML architectures on GCP , with Vertex AI for scalable pipelines.
- Implement MLOps best practices using MLflow, Kubeflow, CI/CD , and cost-aware deployment strategies.
What We’re Looking For:
- 7–10+ years of hands-on experience in Machine Learning and MLOps .
- Proven experience deploying ML models into real production environments .
- Strong skills in Python and SQL .
- Experience with TensorFlow and/or PyTorch .
- Applied ML experience in pricing, forecasting, optimization, or supply chain .
- Strong cloud experience, with GCP and Vertex AI preferred .
Nice to Have:
- Vertex AI pipelines in production
- MLflow / Kubeflow at scale
- Cloud certifications (GCP preferred)
- Experience with semantic search or vector databases
Why This Role:
- High-impact ML work tied directly to business outcomes
- Senior IC ownership and architectural influence
Note: This role requires substantial real-world ML experience