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 scale AI pipelines that generate, evaluate, and optimize interactive ad creatives using LLMs, VLMs, and multimodal models to boost engagement and conversions for global apps and games.
Remote | Must be in LATAM | Part-Time, potential Full-Time or Side Gig About Futureproofing Futureproofing is a talent platform focused on embedding high-caliber engineers into startups building real AI-driven…
About Us First impressions matter. TaskRay is on a mission to ensure businesses get off to a great start with a flawless customer experience once the opportunity is marked Closed Won. TaskRay is the leader in post-sale…
Designs and deploys secure, explainable AI systems for high-stakes environments by translating customer needs into safety-first technical plans.
Designs and builds scalable machine-learning systems on Google Cloud, collaborating with data scientists and engineers to deploy AI solutions and MLOps platforms for enterprise clients.
Principal AI Engineer builds and deploys production-grade agentic AI systems for Mastercard, focusing on multi-agent orchestration, tool integration, safety, and reliability across fintech and AI domains.
Develops AI agents and LLM-based services to enhance trading systems within a bank's Financial Markets division, focusing on RAG pipelines, agent workflows, and financial domain integration.
Build and ship full-stack features and LLM-powered tools for an AI-forward school platform, working directly with founders and senior engineers in Austin.
Trainee AI Engineer program teaching Python, AI models, and cloud certifications to prepare entry-level candidates for AI/data roles with job placement support.
Entry-level AI Engineer role focused on developing AI applications using Python and Azure AI tools, with training and certification support.
Lead a team building cloud-native AI and big-data services for Equifax’s fintech products, using Java/Spring Boot, GCP, Kubernetes, and Apache Beam.
Build and deploy AI agents using LangChain/LangGraph on GCP, leading a team to architect cloud-native, scalable systems and mentor engineers while integrating cutting-edge LLMs and MLOps practices.
Design and deploy AI-powered copilots and agentic solutions using Microsoft’s AI stack (Copilot Studio, Azure AI Foundry) and Python, integrating LLMs and RAG for enterprise clients.
Senior AI Engineer at PwC’s India Acceleration Center, designing and running experiments with LLMs and AI agents to evaluate tools and produce client-ready insights using Python and cloud platforms.
Build and deploy AI solutions for PwC’s Deals Advisory practice using Python, FastAPI/Streamlit, and cloud AI services like Azure OpenAI to solve client challenges in forensic accounting and compliance.
AI engineer in PwC’s Deals Advisory team applies forensic tech and data analytics to detect fraud, analyze financial records, and support regulatory investigations for global clients.
Build and deploy GenAI applications using Python, LLM frameworks (LangChain/Semantic Kernel), and cloud-native tools (Kubernetes, Azure/AWS) to create scalable AI solutions for clients.
Builds and deploys scalable machine-learning solutions for enterprise clients, working with MLOps platforms, cloud tools, and AI frameworks like TensorFlow and PyTorch.
Build and deploy scalable machine-learning solutions on Google Cloud for enterprise clients, collaborating with data scientists and engineers to implement MLOps pipelines and AI observability tools using Python and SQL.
Build production-grade AI agents that automate high-stakes workflows in education, such as drafting university shortlists and triaging applications, using Python, orchestration frameworks, and evaluation infrastructure.
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