Clera
Model Engineer
About this role
Join a founding AI engineering team building intelligent infrastructure systems for enterprise networking. You'll develop machine learning models for fault prediction, network state modeling, and autonomous repair, working across hardware and software in a fast-growing startup with proprietary domain data.
What you'll do
- Train end-to-end ML models for fault prediction, network state modeling, and autonomous corrective action
- Build multi-modal models over structured networking data and implement function-calling for autonomous network-wide decisions
- Evaluate model performance in real-world hardware and virtualized environments, iterating for reliability and efficiency
- Deploy and monitor models in production using MLOps practices and automation pipelines
- Collaborate with hardware and software teams to shape technical direction and research organization culture
- Present findings and model insights to both technical and non-technical stakeholders
What they're looking for
- Machine learning model training and development
- Python programming
- PyTorch or TensorFlow frameworks
- MLOps and model deployment
- Distributed systems and telemetry analysis
- Anomaly detection and fault prediction
- Strong computer science fundamentals
- Cross-functional communication and stakeholder management
Benefits
- Competitive salary of $200,000–$300,000 USD annually
- Opportunity to work on frontier AI for infrastructure
- Access to proprietary dataset and full-stack system visibility
- Early-stage startup environment with significant impact potential
- On-site collaboration in San Francisco (Mission District)
Opens the application — the Jobs AI extension fills it for you. Set up autofill
Opens the official application on the employer’s site. No login required.
Clera
Clera builds an agentic operating system that automates complex workflows and processes through AI agents, with a platform designed to simplify distributed infrastructure management for developers. The company is hiring Founding Engineers, Customer Engineers, and Product Engineers to develop both backend systems and user-facing interfaces across their AI automation products.
View all jobs at CleraLikely interview questions
- Walk us through a specific ML project where you built models for infrastructure monitoring or systems optimization—what were the biggest challenges?
- How have you approached anomaly detection or fault prediction in distributed systems, and how did you validate model performance in production?