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Head of AI

AIFund
USA
Full-time
Senior · 8+ years experience
Hybrid
Discovered 1 weeks ago
LangChainLlamaIndexRayHugging FaceLLMOpsCI/CD
Free

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Key skills for this role

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  • Define and lead the company’s AI roadmap, from foundational research to applied innovation.
  • Build and manage a world-class AI organization, including ML engineers, data scientists, and research scientists.
  • Design and implement scalable AI/ML infrastructure, including data pipelines, model training frameworks, and evaluation systems.
  • Integrate LLMs, multimodal models, RAG systems, and diffusion models into practical enterprise workflows.
  • Partner with engineering and product teams to transform research into production-grade AI features.
  • Lead the development of internal tools and APIs that accelerate AI experimentation and deployment.
  • Champion AI safety, ethics, and responsible model use within the company.
  • Collaborate with customers to understand their domain challenges and translate them into AI-driven solutions.
  • Stay at the frontier of AI research—evaluating new architectures, foundation models, and trends in GenAI and MLOps.
  • Represent ResolveGrid.ai externally at conferences, in publications, and with strategic partners.
  • Advanced degree (MS or PhD) in Computer Science, Artificial Intelligence, or related field.
  • 8+ years of hands-on experience in AI/ML research, development, and deployment.
  • Deep expertise in LLMs, multimodal systems, retrieval-augmented generation (RAG), and AI agents.
  • Experience leading technical teams and mentoring top-tier engineering and research talent.
  • Proven track record of building AI systems from concept to production in fast-paced environments.
  • Strong command of MLOps and LLMOps, including CI/CD pipelines, monitoring, evaluation, and lifecycle management.
  • Entrepreneurial mindset: thrives in early-stage startups and can balance vision with practical execution.
  • Excellent communication skills with the ability to translate complex AI concepts to diverse audiences, from technical teams to executives and investors.
  • Experience in industrial automation, robotics, or enterprise SaaS.
  • Contributions to open-source AI projects or published research.
  • Familiarity with vector databases, multimodal embeddings, and orchestration frameworks (e.g., LangChain, LlamaIndex, Ray, or Hugging Face).
  • Experience with AI compliance, safety, or model governance frameworks.

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