ML Engineer

carbon.talent is always recruiting for ML Engineers who can take models from notebook to production. ML Engineers in our pool own the full lifecycle: feature stores, training pipelines, model registries, serving infrastructure, and monitoring. If you are as comfortable with Kubernetes as you are with loss functions, Carbon wants to know you. What we look for: - Production ML experience — model serving, A/B testing, monitoring for drift - MLflow or a comparable experiment tracking and model registry tool - Python, plus working knowledge of cloud ML services (SageMaker, Vertex AI, or Azure ML) - Familiarity with feature engineering at scale (Feast, Tecton, or custom) - 4+ years of engineering experience, with at least 2 in ML infrastructure This is a talent pool role, not a specific company vacancy. All applicants go through the Carbon vetting process. Applications reviewed within 5 business days.