AI Engineer

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September 10

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Pierce Professional Resources

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Enterprise • Recruitment • Consulting

Pierce Professional Resources is a company specializing in technical and workforce solutions aimed at helping businesses evolve. They offer a range of services including technical staffing, automation and AI, cloud solutions, data modernization, digital transformation, and UI/UX consulting. Additionally, they provide agile leadership coaching, PMO services, and assist with transactional mergers and acquisitions. With over 30 years of experience, Pierce Professional Resources emphasizes delivering exceptional technical solutions and personalized services for their clients, aiming to optimize operations and drive innovation. They focus on building partnerships by deeply understanding client needs and providing customized solutions to achieve success.

11 - 50 employees

Founded 2003

🏢 Enterprise

🎯 Recruiter

📋 Description

• Design, implement, and optimize advanced AI systems balancing quality, performance, and cost. • Architect inference and RAG pipelines; design manager/worker agent patterns with deterministic fallback mechanisms for reliability. • Build robust evaluation harnesses and develop simulation-based training pipelines to improve model robustness. • Tune AI systems across quality, latency, and cost dimensions for scalable production performance. • Run A/B tests and continuous feedback loops to measure system performance and guide improvements. • Collaborate with product and design teams to ensure AI outputs integrate into workflows with intuitive, high-quality UX.

🎯 Requirements

• Strong background in machine learning, AI systems, or applied research. • Hands-on experience with inference optimization and retrieval-augmented generation (RAG). • Familiarity with multi-agent or distributed system design. • Experience building evaluation frameworks, test harnesses, or simulation-based training environments. • Skilled in performance tuning (latency, throughput, cost efficiency). • Proficiency in Python and ML/AI frameworks (PyTorch, TensorFlow, LangChain, Ray, etc.). • Bonus: Experience with A/B testing, feedback loops, and integrating AI with front-end UX.