Adaption Labs

Build production agent systems that plan, use tools, recover from failures, and improve over time. The role requires 5+ years of production ML or backend experience, LLM or agent deployment experience, and expertise in evaluation, tracing, observability, and agent architecture.

Own inference-stack cost and performance by optimizing serving, caching, batching, quantization, decoding, routing, and GPU execution. The role requires 5+ years in ML systems, inference infrastructure, or performance engineering, plus strong Python and systems-language skills.

Build and own the secure multi-tenant platform connecting enterprise customers to inference infrastructure, including public APIs, tenant isolation, metering, entitlements, and enterprise access controls. Requires 5+ years of backend, infrastructure, or platform engineering experience and strong Python and API design skills.

Founding North America GTM leader to architect the sales playbook for a category-defining adaptive AI product. Full-cycle ownership from outbound to close, market feedback to product team, and GTM stack setup. Requires 4-8 years early-stage sales experience, technical AI fluency, and founder-like conviction.

8-month modelling residency embedded in production and research projects, focusing on adaptive algorithms, real-time learning, model efficiency, and cross-stack optimization. Requires Python, deep learning frameworks, and ML optimization experience.

This is a research role focused on building models that continuously evolve with the world, with a focus on efficiency, gradient-free exploration, real-time learning, and interface design. The role requires strong programming skills and expertise in model optimization techniques.

Applied Scientist drives research in efficient, adaptive ML including online learning and gradient-free methods, implements production ML systems, and shapes research/product roadmap. Requires 3-4 years ML experience deploying real-world systems.

Conducts research on efficient AI systems focusing on real-time adaptation, model efficiency, and cross-stack optimization. Requires PhD or equivalent, 4-5+ years industry experience, and deep ML expertise including PyTorch/JAX and optimization techniques.