Applied AI Researcher / Founding Engineer

Job Type: Remote / Full-time / B2B About Us (https://pergolastudio.co/) Pergola Studio is an early-stage startup with a bold vision: to build next-generation AI platforms that push the boundaries of what’s possible in applied machine learning. Current state-of-the-art models can produce impressive results, but at a cost that is margin-dilutive for SaaS businesses using these tools, and inhibits the ability to implement AI-driven performance feedback loops at scale. We are in the process of solving that tension. Our founders have a track record of delivering complex technical products and are now setting out to build something ambitious with a small but elite team. Join us in building a world-class Foundational AI Lab focused on creating the next generation of highly efficient AI models for marketing. You'll own a family of vertically specialized distilled models - from research and training to optimization, evaluation, and production deployment - as they become the company's core technology. Your Role As a Applied AI Researcher / Founding Engineer, you will work directly with the CEO to define and execute the technical roadmap. You will make critical architectural decisions, lead the development of our platform, and shape features from scratch. This role combines hands-on engineering with research and strategic leadership: you’ll both build and manage. Responsibilities: - Own the entire technical foundation of the company - from system architecture to deployment. - Design, fine-tune, and implement cost-efficient, scalable AI models for real-world use. - Cover the whole model lifecycle management: training, fine-tuning, scaling, and monitoring. - Collaborate with leadership to align technology with business strategy. - Manage the full lifecycle: infrastructure, model training, deployment, and optimization. Preferred Qualifications - Strong software engineering background with Python. - Experience building production AI systems using modern agent frameworks. - Hands-on experience with agentic frameworks such as LangGraph, LangSmith, LangFuse, CrewAI, LlamaIndex, or similar ecosystems. - Strong knowledge of NumPy, SciPy, machine learning fundamentals, and data processing. - Experience integrating LLMs, multimodal models, and external tools into real-world applications. - Familiarity with cloud infrastructure, deployment, monitoring, and scaling. - Understanding of prompt engineering, RAG architectures, evaluation frameworks, and AI observability. - Experience with MCP servers, tool calling, and agent orchestration. You would really stand out if you have: - PhD or advanced degree in Computer Science, Mathematics, AI/ML, or a related field is a plus Authorship of research papers in AI