We’re looking for a Machine Learning Engineer to build and deploy production-grade AI systems. In this role, you’ll take models from research to real-world applications, designing, optimizing, and scaling systems that power critical workflows across the enterprise.
You’ll work closely with research, product, and engineering teams to turn cutting-edge capabilities into reliable, high-performance systems in production.
Key ResponsibilitiesModel Development & Deployment: Build, fine-tune, and deploy machine learning models into production environments
Systems Engineering: Design scalable pipelines for training, inference, evaluation, and monitoring
Performance Optimization: Improve latency, throughput, cost efficiency, and reliability of ML systems
Data & Infrastructure: Work with large-scale datasets and integrate models with internal systems and APIs
Cross-Functional Collaboration: Partner with product and engineering teams to deliver end-to-end AI features
Evaluation & Monitoring: Implement robust evaluation frameworks, observability, and feedback loops
Education: Bachelor’s or Master’s in Computer Science, Engineering, or related field (PhD optional, not required)
Technical Skills: Strong proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, JAX)
Production Experience: Experience deploying and maintaining ML systems in production environments
Systems Knowledge: Familiarity with distributed systems, data pipelines, and cloud infrastructure (e.g., AWS, GCP)
Practical ML Expertise: Experience with model training, fine-tuning, evaluation, and iteration at scale
Skills Required
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- Strong proficiency in Python
- Experience with modern machine learning frameworks such as PyTorch, TensorFlow, or JAX
- Experience deploying and maintaining machine learning systems in production environments
- Familiarity with distributed systems, data pipelines, and cloud infrastructure such as AWS or GCP
- Experience with model training, fine-tuning, evaluation, and iteration at scale
- PhD
What We Do
Eragon is a San Francisco-based startup building an agentic AI operating system for enterprise work. The platform connects a company's tools, data, and communication channels, then trains custom proprietary AI models on that data so businesses own their intelligence and model weights. Deployed agents run autonomously to monitor, act, learn, and escalate tasks, letting employees manage operations — from onboarding to invoice approval — through natural language prompts instead of traditional software interfaces, with a security-first approach that keeps client data inside their own environments.
