ResolveGrid.ai is redefining how industrial companies manage complex field engineering operations. Our founders combine deep industry expertise with Silicon Valley experience. ResolveGrid.ai is backed by Andrew Ng’s AI Fund and other notable investors. ResolveGrid.ai leverages cutting-edge AI to bring unprecedented efficiency, intelligence, and adaptability to industrial workflows.
Resolvegrid is already trusted by over 20 enterprise customers. This is a rare chance to shape the technical DNA and product foundation of a platform that will transform how industries scale. You will work directly with our CEO and founding team to build next-generation AI systems for the industrial sector. This is a hybrid role that will be based in Southern California.
Responsibilities for the Role Include:
Define and lead the company’s AI roadmap, from foundational research to applied innovation.
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 for the Role Include:
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 for the Role Include:
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.
