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.
Build and maintain Later’s cloud infrastructure, Kubernetes clusters, and MLOps pipelines to deploy AI models reliably using AWS, Terraform, and CI/CD tools.
A Data Engineer / Analytics Engineer builds and maintains the client's data platform, developing data models and transformation pipelines with DBT as the ETL/ELT tool and heavy SQL, including staging/marts layers, testing, documentation, and query optimization, on-site in Sant Cugat del Vallès.
Senior full stack engineer building VOICEB.ai's autonomous AI voice-agent platform: backend services, APIs, integrations (Salesforce, HubSpot, Twilio, SIP/WebRTC) and internal tooling. Remote within Spain, owning features end to end on a small team with the CTO, using a modern JS/TS stack (React/Node) on AWS/GCP.
Site Reliability Engineer at The Voleon Group (an AI/ML-driven investment manager) in London, working at the intersection of production operations and software development: improving and monitoring production-critical trading systems and data pipelines, debugging Python code, automating workflows, and sharing an on-call rotation. Core stack includes Python, Linux, and SQL, with exposure to tools l
Designs and deploys large-scale AI/ML workloads on GPU cloud infrastructure, advising key customers and optimizing performance while collaborating with sales and product teams.
Nscale, a GPU cloud provider for AI workloads, is hiring a Staff Security Engineer to lead product and platform security: hands-on threat modeling, architecture reviews, vulnerability management (CVSS triage and remediation), running bug bounty/responsible disclosure programs, and supporting incident response across its cloud platforms and hyperscale GPU clusters.
Senior/Staff Data Engineer owning and evolving the data platform (ETL/ELT pipelines, data warehouse, data quality) for Cerebras, an AI chip company. Day-to-day involves building production data pipelines in Python and SQL on cloud infrastructure (AWS/GCP/Azure) while partnering with analytics and engineering stakeholders.
Product Manager owning Suno's teams & business revenue line — defining offerings for professional creatives, teams, and enterprises, running pilots/betas, and building the collaboration, admin, security, and compliance (SOC 2, GDPR) foundations to take B2B products from first customers to repeatable revenue. On-site in NYC 5 days/week.
Designs, builds, and deploys production-grade AI systems and ML pipelines, focusing on scalable implementations and collaboration with cross-functional teams.
Design and deliver enterprise-grade generative and agentic AI systems on AWS, leveraging Amazon Bedrock, Strands Agents, and related services to build scalable, secure AI platforms.
Leads the design, delivery, and adoption of AI/ML systems directly within client environments, owning architecture decisions and driving solutions from research through production at scale.
Principal engineer designing and shipping production-grade multi-agent AI systems on AWS, leading architecture across cloud, data, and AI/ML while mentoring teams and setting technical direction.
Lead the design and delivery of AI/ML systems, owning architecture decisions and driving solutions from research through production at scale.
Lead end-to-end delivery of enterprise-grade AI agents, defining behavior, running evals, and shipping production solutions in 30–45 days using AWS AI services and modern agentic frameworks.
Lead end-to-end AI product delivery for enterprise GenAI and agentic AI engagements, defining agent behavior, running evals, and shipping production-grade solutions in 30–45 days.
Lead end-to-end architecture for cloud, data, and AI systems, designing scalable, secure solutions and mentoring teams to ship production-ready AI in 30–45 days.
Lead platform engineering for multi-environment cloud systems, defining DevSecOps standards and Kubernetes infrastructure to deploy and scale AI/ML workloads rapidly.
Lead end-to-end UX/UI design for AI-powered enterprise products, owning design systems, research strategy, and mentoring teams to ship human-centered AI workflows.
Lead the design of cloud, data, and AI systems for enterprise clients, setting technical direction and mentoring teams to ship production-ready AI in 30–45 days.
Hands-on technical lead who designs, builds, and scales production-grade AI systems: defining architecture, leading ML/LLMOps implementation (RAG, agentic orchestration, inference pipelines, AWS), and mentoring engineers. Requires 5+ years in AI/ML engineering with strong Python and distributed systems experience.
We couldn't check your fit for this role — add a CV to your profile to see it next time.