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 lead Mercor’s code-search systems: hybrid retrieval (dense embeddings + BM25) that routes coding tasks to the right models and turns natural-language questions into precise code retrieval at scale.
Build and deploy ML models end-to-end: train, optimize, and package solutions while setting up MLOps pipelines, monitoring, and data governance for production AI systems.
Lead the design and deployment of an end-to-end AI architecture for Mercedes-Benz vehicles, integrating cloud and embedded AI across domains like ADAS and cockpit.
Lead AI engineering for classified systems: design, deploy, and secure LLMs and ML models in air-gapped environments while aligning with government accreditation and responsible-AI practices.
Lead AI/ML engineering for classified systems: design, deploy, and secure LLMs and retrieval pipelines in air-gapped environments while aligning with government accreditation and responsible-AI standards.
Designs and deploys secure, rugged embedded systems integrating CPUs/GPUs/TPUs/FPGAs for edge computing, optimizing AI models for real-time inference and hardening against cyber/physical threats in mission-critical environments.
Build and optimize generative AI models and inference pipelines for Snapchat’s AR and creative tools, delivering scalable, on-device experiences for millions of users.
Build and deploy AI models for edge devices: port vision/speech models to NPU-enabled SoCs, extend AI tooling for hardware-aware development, and create reference designs for smart-home and surveillance use cases.
Build and optimize generative AI models for Snapchat, including LLMs, video generation, and AR, focusing on efficient inference and on-device deployment.
As a world-leading OEM, Mercedes-Benz seeks experts who are passionate and enthusiastic about applying AI technologies to the automotive industry. We are specifically looking for self-motivated and knowledgeable…
Build and deploy quantized large language models for in-vehicle AI, focusing on PTQ, QAT, and low-bit inference to ensure numerical consistency and performance on XPENG’s Turing AI chip.
Build and deploy quantized large language models for in-vehicle AI, focusing on PTQ, QAT, and low-bit inference to optimize performance on XPENG’s Turing AI chip.
Develops and optimizes model-compression tools (quantization, pruning, distillation) for LLMs and generative models to run efficiently on Intel AI hardware.
Architect and deploy AI systems for semiconductor manufacturing, focusing on model selection, governance, and integration across engineering workflows and enterprise platforms.
Our client is a fast-growing AI-driven fintech company building next-generation digital products for the financial services industry. They leverage machine learning and modern cloud technologies to deliver highly…
About Sunset At its core, Sunset was founded to help founders. We started by supporting startups through shutting down, but we have since expanded into unlocking a new revenue stream for all types of businesses. In…
Optimize and deploy large language models for enterprise customers, tuning inference engines and post-training pipelines to meet performance targets.
Company: Qualcomm Middle East Information Technology Company LLC Job Area: Engineering Group, Engineering Group > Systems Engineering General Summary: About Us As a leading technology innovator, Qualcomm pushes the…
Build and deploy ML/AI models end-to-end, from data exploration to production, using Python, PyTorch/TensorFlow, and cloud platforms like AWS/GCP/Azure.
The Company: Faraday Future is a California-based technology company focused on the design, engineering, and development of intelligent, connected electric vehicles and related artificial intelligence–enabled…
We couldn't check your fit for this role — add a CV to your profile to see it next time.
