Head of AI Research

Harnham; Berkeley (CA); On-site; USD 300,000 - 350,000; Full time

Job summary

Harnham invites applications for the Head of AI Research, a mission-driven chief scientist role in Berkeley. You will set the scientific strategy, oversee research operations, and lead interdisciplinary teams toward high-impact outcomes, reporting to the CEO and joining the executive leadership.

Candidates bring 15+ years in AI research and a PhD, with a track record of building teams, managing budgets, and advancing responsible AI.

Qualifications

• PhD in Machine Learning, CS, EE, or related field.
• 15+ years leading AI research or large-scale AI programs.
• Proven leadership of research organizations and senior teams.
• Strong professional network within AI research and industry.
• Ability to recruit and develop senior scientific talent.

Responsibilities

• Define and oversee a multi-year scientific roadmap aligned with mission and objectives.
• Ensure collaboration between AI research and domain science teams for impactful outcomes.
• Maintain high scientific rigor, reproducibility, and integrity.
• Lead, mentor, and develop senior research leaders and teams.
• Partner with leaders to prioritise initiatives, allocate resources, and ensure execution.
• Represent the organization at external events and with funders.

Skills

AI leadership

Strategic planning

Cross-functional

Executive comms

Talent development

Education

PhD in ML/CS

Job description

Head of AI Research

$300k-$350k

Overview

A mission-driven research organisation is seeking a Chief Scientist to lead its scientific strategy, research operations, and interdisciplinary research teams. Reporting directly to the Chief Executive Officer and serving as a member of the executive leadership team, this individual will oversee multiple research functions and ensure alignment between scientific objectives, organisational priorities, and long-term impact. This role focuses on building and leading a high-performing research organisation rather than serving as an individual contributor. The successful candidate will bring deep expertise in artificial intelligence, substantial leadership experience, and the ability to integrate technical and scientific disciplines into a cohesive research strategy.

Key Responsibilities

Scientific Leadership & Strategy

• Define and oversee a multi-year scientific roadmap aligned with organisational mission and objectives.
• Ensure close collaboration between AI-focused research and domain science teams to drive meaningful scientific outcomes.
• Maintain high standards of scientific rigor, reproducibility, and research integrity.
• Monitor relevant developments in machine learning, computational science, behavioural research, and related disciplines, translating insights into strategic opportunities.

Research Organisation Leadership

• Lead, mentor, and develop senior research leaders and multidisciplinary teams.
• Design organisational structures, staffing plans, and growth strategies to support research priorities.
• Recruit and retain exceptional scientific and technical talent, particularly for senior leadership positions.
• Partner with programme and operational leaders to prioritise initiatives, allocate resources, and ensure effective execution.
• Foster an inclusive, collaborative, and high-performing research culture.

Executive Leadership

• Serve as a strategic partner to executive leadership on organisational direction and long-term planning.
• Align research priorities with fundraising, communications, and organisational initiatives.
• Present research strategy, progress, and key decisions to leadership, funders, boards, and external stakeholders.
• Support external communications by ensuring scientific findings and organisational priorities are accurately represented.

Financial Management

• Own research budget planning and spending within approved parameters.
• Develop and manage multi-year research budget forecasts in partnership with organisational leadership.
• Monitor expenditures and proactively identify significant budgetary changes or risks.

External Engagement

• Represent the organisation at scientific, industry, and professional events.
• Develop partnerships with academic institutions, government organisations, nonprofits, and research collaborators.
• Contribute to publications, thought leadership, and public-facing scientific communications.
• Expand external research networks through fellowships, internships, and academic outreach programmes.

Culture & Ethical Leadership

• Promote cross-functional collaboration and transparent knowledge sharing.
• Create an environment that values respect, inclusion, and diverse perspectives.
• Encourage participation from researchers at all levels in scientific planning and decision-making.
• Uphold strong ethical standards in research design, data usage, interpretation, and communication.

Required Qualifications

Education

• PhD in Machine Learning, Computer Science, Electrical Engineering, Computational Biology, or a closely related discipline.
• Strong scientific credibility and research accomplishments, though an active publication record is not required.

Experience

• 15+ years of experience spanning AI research, large-scale AI implementation, or a combination of both.
• Demonstrated success leading research organisations, technical teams, or advanced AI programmes.
• Significant experience evaluating research quality and managing senior researchers or technical leaders.
• Experience building teams, setting strategic direction, and maintaining scientific standards.
• Strong professional network within the AI research and technology community.
• Ability to recruit and develop senior-level scientific talent.

Technical Expertise

• Deep understanding of modern AI and machine learning methodologies.
• Familiarity with foundation models, large-scale model training, and production-scale AI systems.
• Experience assessing research quality across interdisciplinary environments.
• Understanding of quantitative scientific research methods and data-driven experimentation.

Leadership Skills

• Proven ability to lead complex, multidisciplinary research organisations.
• Strong organisational judgement and strategic decision-making skills.
• Excellent communication skills with executive, scientific, funding, and public audiences.
• Ability to bridge different research cultures and disciplines effectively.
• Passion for mission-oriented scientific research and long-term impact.

Preferred Qualifications

• Experience working in both academic and commercial research environments.
• Background applying AI to scientific or natural-world research domains.
• Familiarity with machine learning for audio, speech, computer vision, or related data modalities.
• Experience in nonprofit, research institute, mission-driven, or field-based scientific organisations.
• Knowledge of responsible AI frameworks and ethical research practices.