An early-stage team building the intelligence layer for enterprise workflows.
Full-Stack ML Systems Engineer
You are an engineer who sees machine learning not as a black box but as a system requiring robust orchestration and clear visibility. In this founding-level role, you will construct the full-stack infrastructure that powers workflow automation, bridging the gap between experimental LangChain prototypes and production-grade Kubernetes environments. Your work involves hardening Dockerized services, designing observability pipelines with Grafana, and ensuring data insights flow seamlessly into Tableau dashboards for enterprise clients.
What they're looking for
- 5+ years of experience shipping full-stack applications with deep integration of Python-based ML models.
- Proven expertise deploying and managing containerized workloads on Kubernetes within enterprise environments.
- Strong background in building observability stacks using tools like Grafana to monitor system health and model performance.
- Experience integrating LLM frameworks such as LangChain into scalable, reliable backend architectures.
- Ability to translate complex data outputs into actionable business intelligence visualizations using Tableau.