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 optimize AI agents for Google Cloud’s Applied AI suite, focusing on recommendation systems, skill discovery, and performance tools for conversational agents.
Build and optimize AI-driven speech technologies (TTS/STT) for an interactive gaming platform, leveraging machine learning to enhance AI character experiences.
Lead AI/ML projects to build safety and security mitigations for Google Workspace, including LLM-based auto-raters and prompt-injection classifiers, collaborating with DeepMind and Workspace teams.
Build, deploy, and maintain AI/ML models including LLMs and Agentic AI systems using cloud platforms like Azure and GCP to solve business and scientific problems.
Build and scale AI systems to surface high-quality merchants and shopping experiences for Pinterest users, collaborating across teams to improve discovery and business reach.
Lead the architecture and development of large-scale RAG and NLP systems for vertical AI platforms, using PyTorch, vector databases, and probabilistic modeling to deliver predictive intelligence for high-stakes industries.
Build AI-enhanced features and scalable APIs for a high-performance database, integrating AI capabilities with user-friendly interfaces.
Forward-deployed ML engineer partners with clients to deploy Mistral’s AI models, fine-tuning and integrating them into production systems while bridging technical and business stakeholders.
Build and deploy AI models, LLMs, and NLP tools to enhance customer interactions and workflows at a customer-experience AI platform.
Build and deploy Python-based data pipelines and ML models for financial services, using Spark, TensorFlow, and SQL to analyze risk and support decision-making.
Lead AI product initiatives for Edge devices, optimizing ML models for petabyte-scale sensor and video data to improve physical operations like safety and efficiency.
Build and deploy ML models to improve job-matching for Indeed’s users, using Python, TensorFlow/PyTorch, and cloud platforms.
Build and maintain the data pipelines and tooling that feed AI/ML services for a cloud-based healthcare platform, enabling model development, deployment, and monitoring at scale.
Lead firmware design for edge AI accelerators, optimizing memory, DMA, and power while co-designing hardware specs and guiding customers on deploying PyTorch/TensorFlow models on custom silicon.
Build and maintain ML pipelines to optimize marketing campaigns using Python, PyTorch, or TensorFlow in a remote role.
Build and scale face-recognition systems using PyTorch/TensorFlow, own end-to-end ML pipelines on AWS, and lead fairness analysis for biometric models in production.
Design and build cloud-native AI agents and ML systems for Autodesk’s PDM/PLM workflows, focusing on LLM, RAG, MCP, and agentic architectures in production.
Build and maintain scalable Java/Python microservices and integrate ML models for an international institution using REST APIs and cloud infrastructure.
Build and maintain Python-based banking backend services and ML/AI pipelines, integrating with financial systems and ensuring regulatory compliance.
Build and maintain scalable Java/Python microservices and integrate ML models for a European institution, using REST APIs and cloud practices.
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