Point your AI agent at freehire and let it find you a job. A CLI and an MCP server over the whole job API — no browser.
About ActAI There are over 5 billion users using basic applications today such email, notes, tasks, calendar and they're not AI-native. Our mission is to build proactive applications for anyone in the world, who…
Hands-on ML technical lead owning the end-to-end machine learning stack — data pipelines, training/fine-tuning, evaluation, inference, and deployment — behind AI-native productivity apps. Remote role based in China; core stack is Python, PyTorch/JAX, and GPU-based training and inference systems.
The Lead Engineer, Machine Learning will build and scale production-ready AI systems, managing the full model lifecycle from training to deployment. The role focuses on creating reliable, high-performance inference systems using Python, PyTorch, and JAX to power proactive, AI-native applications.
Principal ML Engineer building AI-native productivity apps for tasks and workflows. Responsible for the end-to-end ML lifecycle, including training pipelines, evaluation systems, and high-performance GPU inference using Python, PyTorch, or JAX. Focuses on turning research into reliable, scalable production systems for long-running workflows.
Staff ML Engineer owning the end-to-end ML execution layer at an AI-native productivity startup — building training/fine-tuning pipelines, evaluation systems, and high-performance GPU inference to turn large models into reliable production systems for proactive everyday apps (email, notes, tasks, calendar). Stack: Python, PyTorch/JAX, GPU infra.
Technical Product Manager defining end-to-end requirements for LLM-based AI systems, working closely with ML and engineering teams on system design, evaluation frameworks, and product quality in a zero-to-one startup environment.
The Product Owner for an AI Email App defines AI capabilities and system behavior to enhance user workflows with minimal prompting, focusing on reliability, context, and real-world task completion. They collaborate with ML and engineering teams to balance quality, latency, cost, and UX while ensuring predictable, trustworthy AI interactions.
Lead Software Engineer for an AI-native email app, owning architecture across backend, mobile, and desktop while leading a small senior engineering team to turn AI/LLM capabilities into reliable, shippable product experiences.
About the Role There are over 5 billion users using basic applications today such email, notes, tasks, calendar and they're not AI-native. Our mission is to build proactive applications for anyone in the world, who…
The Principal Software Engineer will lead a team to build a reliable, AI-native email application by designing backend and client-side architectures that integrate LLM capabilities. This hands-on role involves managing complex workflows, ensuring system reliability, and partnering with ML leadership to deliver a high-quality product.
Staff engineer owning the engineering layer for an AI-native email/app product, designing reliable backend systems, APIs, and client apps that integrate with ML/LLM capabilities while leading a small senior team.
iOS Software Engineer building AI-native iOS apps with Swift and SwiftUI, focused on AI interaction UX patterns, streaming responses, performance optimization, and on-device inference.
Full stack engineer at ActAI building AI-native product features: designing agent workflows (planning, tool use, failure/recovery), integrating LLMs, memory and external tools, and improving reliability and latency of real-time AI interactions. Stack includes Next.js, Python, Node.js, PyTorch, OpenAI/Anthropic LLMs, SQL/NoSQL, Kubernetes, Docker.
Build AI-native workflows that handle multi-step tasks, integrate LLMs with tools, and ensure reliable, real-time interactions for a proactive smart assistant.
We couldn't check your fit for this role — add a CV to your profile to see it next time.