Head of AI & Machine Learning

Pivotal Solutions, Inc.; San Francisco (CA); On-site; USD 190,000 - 350,000; Full time

Job summary

Pivotal Solutions, Inc. seeks a Head of AI & Machine Learning to lead the development of transformative AI systems. You will drive multi-agent architectures, integrate foundation models, and tailor AI capabilities to business needs, ensuring transparency and regulatory compliance.

You will oversee end-to-end AI initiatives, collaborate with cross-functional teams, and mentor engineers while advancing research and industry impact.

Qualifications

• PhD in Computer Science, ML, AI, or a related field.
• 5+ years of experience in AI/ML research and development.
• Expertise in large language models (LLMs), multi-agent systems, and AI orchestration.
• Experience applying AI in high-stakes domains is valued.
• Proven ability to design and implement agent-based systems for complex tasks.
• Demonstrated success in building transparent and explainable AI applications.
• Proficiency in retrieval-augmented generation for knowledge-intensive tasks.
• Strong understanding of domain-specific data and decision-making processes.
• Experience with privacy-preserving AI techniques and regulatory considerations.
• Ability to translate business needs into robust AI architectures.
• Strong leadership and mentoring skills; excellent communication with non-technical stakeholders.
• Publications in AI/ML or proven industry implementations.
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Hugging Face).

Responsibilities

• Lead the development and scaling of a multi-agent AI platform for end-to-end solutions.
• Enhance integration with foundation models while building custom AI capabilities.
• Design and expand agent workflows for complex tasks and decision-making.
• Develop neural architectures optimized for domain-specific reasoning.
• Create purpose-built AI agents with capabilities beyond general models.
• Engineer orchestration layers for seamless agent collaboration.
• Build systems to extract insights from diverse data sources.
• Design evaluation frameworks for performance, trust, and outcomes.
• Implement intelligence loops for continual knowledge accumulation.
• Create explainable AI decision pathways for transparency and compliance.
• Architect adaptive interfaces evolving with user behavior.
• Design privacy-preserving AI systems to enable personalization.
• Implement regulatory guardrails for industry standards.
• Collaborate with leadership and product teams to integrate AI into products.
• Stay at the forefront of AI innovation through research and application.

Skills

LLMs

Multi-agent systems

AI orchestration

Agent-based systems

Retrieval-augmented generation

Explainable AI

Human-AI interaction

Privacy-preserving AI

Leadership

Communication with stakeholders

Education

PhD in Computer Science, ML, AI or related field

Tools

Python

TensorFlow

PyTorch

Hugging Face

Job 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).