We are looking for an experienced, versatile Founding Software Engineer.
We are building foundation models for tabular data, time series, and ultimately the broader world of structured data. Our goal is to make powerful machine learning dramatically easier to use, customize, and deploy across real-world applications and enterprise environments.
This is a broad, high-ownership role spanning software engineering, backend systems, cloud infrastructure, machine learning platforms, security, and developer tooling.
Responsibilities
- Design, build, deploy, and operate core product and platform capabilities.
- Build production backend services, APIs, SDKs, internal tools, and customer-facing applications.
- Design scalable infrastructure for machine learning training and inference workloads.
- Develop secure deployment options for hosted and customer-managed environments.
- Package and operate containerized applications and GPU workloads.
- Build reliable systems for asynchronous jobs, storage, model artifacts, observability, and auditability.
- Own cloud infrastructure, networking, deployment automation, and CI/CD pipelines.
- Establish engineering practices around architecture, testing, security, reliability, and documentation.
- Make foundational technology decisions and help define the engineering roadmap.
Qualifications
- Significant professional software engineering experience, ideally in an early-stage or high-ownership environment.
- Strong Python skills and experience building production backend systems.
- Experience designing reliable APIs, distributed systems, and asynchronous job-processing architectures.
- Strong experience with at least one major cloud platform: AWS, Azure, or Google Cloud.
- Deep knowledge of containers, databases, networking, cloud storage, and production operations.
- Experience with infrastructure as code, CI/CD, monitoring, logging, and incident response.
- Experience deploying or supporting production machine learning systems.
- Sound understanding of security, identity and access management, encryption, secrets management, and data isolation.
Nice to Have
- Experience with OpenTofu, Terraform, Kubernetes, or similar infrastructure tooling.
- Experience with managed ML platforms such as SageMaker, Vertex AI, or Azure Machine Learning.
- Familiarity with PyTorch, fine-tuning, distillation, distributed training, or model optimization.
- Experience operating GPU workloads or high-performance model-serving systems.Experience with cloud marketplaces, private deployments, or enterprise security reviews.
- Experience deploying enterprise AI agents or agentic workflows.
- Experience building developer tools, Python SDKs, or technical user interfaces.
- Previous founding engineer, technical lead, or startup experience.