We are actively building world-class AI systems.
Hiring will open selectively as deployments scale.
Build production AI systems backed by published methods, peer-reviewed evaluations, and deployed at scale across healthcare, NLP, and trustworthy document systems.
Collaborate with researchers publishing at NeurIPS, ICML, ICLR. Work alongside engineers deploying Bayesian systems, uncertainty quantification, and conformal prediction frameworks.
Ship code that matters. Our platforms handle real-world uncertainty, adversarial conditions, and mission-critical decisions. Every deployment is instrumented, monitored, and continuously validated.
We hire for fit, not velocity. Competitive compensation, equity, flexible remote work, and comprehensive benefits when positions open as systems reach production maturity.
Build production-grade medical AI systems with uncertainty quantification, Bayesian neural architectures, and conformal prediction. Deploy models validated against clinical endpoints, regulatory frameworks, and real-world patient data streams.
Develop deepfake detection systems, document verification pipelines, and adversarial robustness frameworks. Work on blockchain-anchored provenance, zero-knowledge verification, and production anomaly detection for critical documents.
Build transformer-based systems for domain adaptation, causal inference from text, and adversarial attack mitigation. Ship platforms that extract structured insights from unstructured corpora at scale, with calibrated confidence intervals.
Design end-to-end platforms for intelligent web analytics, user behavior modeling, and real-time recommendation systems. Architect React/TypeScript frontends, Python/FastAPI backends, and distributed ML inference serving billions of events.
Research and deploy generative models with safety constraints, factual grounding, and interpretability guarantees. Build systems for synthetic data generation, mixture-of-experts architectures, and test-time compute strategies.
Build infrastructure for reproducible ML research: experiment tracking, distributed hyperparameter optimization, GPU cluster orchestration, and versioned dataset pipelines. Support researchers shipping SOTA results to production.
We maintain a selective pipeline of exceptional candidates. If you are a world-class ML researcher, systems engineer, or full-stack developer with production experience in AI safety, uncertainty quantification, or large-scale deployment, we want to hear from you.
Send your CV, GitHub/Scholar profiles, and a brief note on which systems interest you most.
careers@terasystems.ai