senior

Hire a AI Engineer

Max Fritzhand builds AI-powered products that drive real business outcomes. As founder of Bolta, he created an AI platform with 30+ tools for social media automation, content generation, and productivity — serving 500+ active users. His AI engineering work includes fine-tuning language models, integrating OpenAI and Whisper APIs, implementing ML classification with 97% accuracy, and designing AI workflows that augment human creativity rather than replacing it.

Core Responsibilities

Design and deploy AI-powered features that solve specific business problems — not AI for showcasing

Fine-tune language models and implement prompt engineering for domain-specific content generation

Build ML classification pipelines achieving production-grade accuracy (97% at HandyApp)

Integrate AI APIs (OpenAI, Whisper, custom models) into production web and mobile applications

Architect AI product roadmaps that balance technical capabilities with user needs and business viability

Related Skills

AI & Machine LearningPythonTypeScriptNext.jsProduct Strategy & Leadership
#ai#ml#llm#engineering#product

Frequently Asked Questions

What AI products has Max Fritzhand built and shipped?
Max founded Bolta — an AI platform with 30+ tools including content generators, carousel creators, podcast-to-thread converters, and trending topic analyzers, serving 500+ users. He also implemented ML sound classification (97% accuracy) at HandyApp and built multiple AI-powered public applications.
How does Max Fritzhand approach AI product development differently?
Max starts with the business problem, not the technology. At Bolta, each of the 30+ AI tools was built to solve a specific creator pain point. He validates with real users, measures adoption, and scales what works. His $3k+ in pre-sale revenue and 500+ user base demonstrate product-market thinking applied to AI.
Can Max Fritzhand fine-tune and deploy custom AI models?
Yes. Max has fine-tuned Llama models for specialized content generation, implemented custom ML classification models in Python, and integrated multiple AI APIs into production. He selects models based on cost, quality, latency, and customization potential — building abstraction layers that allow model swapping.

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