Head of AI
Lead AI strategy, research, and execution for industrial AI platform. Build and manage AI teams, integrate advanced models like LLMs and RAG into production, requiring 8+ years experience and MS/PhD.
About the job
Responsibilities
- 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.
Requirements
- 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.
Nice to Haves
- 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.
Skills
LLMs, Multimodal Models, RAG, AI Agents, MLOps, Llmops, LangChain, Llamaindex, Ray, Hugging Face
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