Aim4Hire
Recruitment • HR Tech • B2B
Aim4Hire is a boutique talent agency based in Texas, specializing in recruiting for emerging tech startups. The company focuses on quality representation of clients' brands, cultures, technologies, and futures. Aim4Hire recruits top talent across various verticals including AI/Data, Cybersecurity, Machine Learning, IoT & Robotics, Energy/Grid Tech, eCommerce, FinTech, and Healthcare Tech. They are known as a trusted recruiting partner for emerging tech sectors and have a notable list of tech startup clients.
11 - 50 employees
Founded 2020
🎯 Recruiter
👥 HR Tech
🤝 B2B
AI Engineer
Job not on LinkedIn
July 2
Aim4Hire
Recruitment • HR Tech • B2B
Aim4Hire is a boutique talent agency based in Texas, specializing in recruiting for emerging tech startups. The company focuses on quality representation of clients' brands, cultures, technologies, and futures. Aim4Hire recruits top talent across various verticals including AI/Data, Cybersecurity, Machine Learning, IoT & Robotics, Energy/Grid Tech, eCommerce, FinTech, and Healthcare Tech. They are known as a trusted recruiting partner for emerging tech sectors and have a notable list of tech startup clients.
11 - 50 employees
Founded 2020
🎯 Recruiter
👥 HR Tech
🤝 B2B
📋 Description
• Lead creation & implementation of RAG systems • Architect multi-agent systems that operate effectively within our platform • Build highly scalable LLM-powered systems that can handle enterprise-level workloads • LLM fine-tuning initiatives to customize models for specific business domains and use cases • Optimize LLM performance, cost, and reliability in production environments • Mentor and develop junior engineers in AI/ML best practices • Evaluate emerging AI technologies for potential adoption
🎯 Requirements
• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field • 8+ years of backend engineering experience in Python • 3+ years of hands-on experience building and deploying machine learning systems • Experience building solutions at scale with large enterprise data
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