Head of AI & Machine Learning

Pivotal Solutions

  • San Francisco, California
  • 2 days ago

    Highlights

    As the Head of AI & Machine Learning, you will lead the development of transformative AI systems, leveraging generative AI and multi-agent architectures to deliver innovative solutions. Build advanced systems to extract insights from diverse data sources, including documents, market signals, and user inputs.

    Numbers & Facts

    LocationSan Francisco, California
    Websitewww.pivotalhire.com

    Description

    As the Head of AI & Machine Learning, you will lead the development of transformative AI systems, leveraging generative AI and multi-agent architectures to deliver innovative solutions. Your work will focus on creating advanced, custom AI models that process complex, multi-modal data and provide actionable insights. Internally, you will enhance operational efficiency through AI-driven systems. Externally, you will redefine user experiences by delivering personalized, transparent, and accessible AI solutions.

    Responsibilities

    • Lead the development and scaling of a multi-agent AI platform to deliver sophisticated, end-to-end solutions.

    • Enhance integration with foundation models while building custom AI capabilities tailored to specific needs.

    • Design and expand agent workflows to handle complex tasks and decision-making processes.

    • Develop specialized neural architectures optimized for domain-specific reasoning and decision-making.

    • Create purpose-built AI agents with capabilities beyond general-purpose models.

    • Engineer proprietary orchestration layers to enable seamless collaboration among AI agents.

    • Build advanced systems to extract insights from diverse data sources, including documents, market signals, and user inputs.

    • Design novel evaluation frameworks to measure performance, trust, and qualitative outcomes.

    • Implement intelligence loops to enable continuous knowledge accumulation from user interactions.

    • Create explainable AI decision pathways to ensure transparency for users and compliance with regulations.

    • Architect adaptive interfaces that evolve based on user behavior and preferences.

    • Design privacy-preserving AI systems to protect sensitive data while enabling personalization.

    • Implement regulatory compliance guardrails to ensure adherence to industry standards.

    • Collaborate with leadership, engineering, operations, and design teams to integrate AI systems into products.

    • Stay at the forefront of AI innovation, researching and applying breakthrough techniques.



    Requirements

    Qualifications

    • PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.

    • 5+ years of experience in AI/ML research and development, preferably at leading AI labs or technology companies.

    • Expertise in large language models (LLMs), multi-agent systems, and AI orchestration.

    • Experience applying AI in high-stakes domains, such as finance or regulated industries, is highly valued.

    • Proven ability to design and implement agent-based systems for complex, real-world tasks.

    • Demonstrated success in building practical AI applications with transparency and explainability.

    • Proficiency in retrieval-augmented generation for knowledge-intensive applications.

    • Strong understanding of domain-specific data and decision-making processes.

    • Background in human-AI interaction design and explainable AI methodologies.

    • Experience building systems that learn from user feedback and improve over time.

    • Deep knowledge of privacy-preserving AI techniques for sensitive data.

    • Ability to translate business needs into robust AI architectures.

    • Expertise in balancing innovation with regulatory and compliance requirements.

    • Strong leadership and mentoring skills with experience guiding technical teams.

    • Excellent communication skills to collaborate with non-technical stakeholders.

    • Commitment to building accurate, reliable, and trustworthy AI systems.

    • Published research in AI/ML conferences or proven industry implementations.

    • Proficiency in Python and relevant ML frameworks and libraries (e.g., TensorFlow, PyTorch, Hugging Face).


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