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Generative Ai Director Jobs in California (NOW HIRING)

As a software engineer, generative ai at WRITER, you'll be at the forefront of expanding human ... You'll report to an engineering director or a senior engineering manager. * We are open to hiring ...

Partner Engineer, Generative AI Responsibilities: * Apply relevant AI and machine learning ... Proactively communicate feedback, updates, status to direct team as well as relevant cross ...

As Head of Generative AI Research, you will shape Visa's GenAI research agenda, collaborate with top academic institutions, publish in premier AI conferences, and work closely with product and ...

As Head of Generative AI Research, you will shape Visa's GenAI research agenda, collaborate with top academic institutions, publish in premier AI conferences, and work closely with product and ...

Responsibilities Apply relevant AI and machine learning techniques to build and launch generative ... to direct team as well as relevant cross-functional teams • Create clear and concise ...

Job Summary We are seeking an experienced and hands‑on Director to lead the strategy ... Lead the evaluation and adoption of generative AI tools, identifying high‑impact opportunities ...

GenAI Art Director Overview We are seeking an AI-native Art Director to lead the development of ... Generative AI Image Creation & Process Development * Personally generate and prompt engineer ...

As the Director, Analyst Relations, you will lead the AR function end to end. You will be the ... The ideal candidate is a compelling storyteller with a deep understanding of AI, generative AI, and ...

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Generative Ai Director information

What does a Generative AI Director do?

A Generative AI Director leads teams in developing and deploying artificial intelligence models that create new content, such as text, images, or music. They oversee the strategic vision, project management, and ethical considerations of generative AI initiatives. This role often involves collaborating with data scientists, engineers, and business leaders to ensure AI solutions align with organizational goals and comply with industry standards. Additionally, the Generative AI Director stays up to date with the latest advancements in AI research and guides the integration of cutting-edge technologies into products and services.

What are the key skills and qualifications needed to thrive as a Generative AI Director?

To thrive as a Generative AI Director, you need deep expertise in AI/ML algorithms, experience leading technical teams, and an advanced degree in computer science or a related field. Proficiency with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms, and familiarity with data privacy standards and relevant certifications (like AWS Certified Machine Learning) are highly valued. Strong leadership, strategic vision, and effective communication skills help drive innovation and align cross-functional teams. These skills are crucial for successfully managing complex AI initiatives, ensuring ethical deployment, and maintaining a competitive edge in a rapidly evolving field.

What are the typical challenges faced by a Generative AI Director when leading cross-functional teams?

As a Generative AI Director, one common challenge is aligning diverse teams—such as data scientists, software engineers, product managers, and designers—toward a unified vision for AI-driven solutions. Balancing innovation with ethical considerations and regulatory compliance is also critical, especially as generative AI evolves rapidly. Additionally, fostering continuous learning while managing stakeholder expectations and resource constraints requires strong leadership, clear communication, and strategic prioritization.

What is the difference between Generative Ai Director vs Data Scientist?

AspectGenerative Ai DirectorData Scientist
Required CredentialsAdvanced degrees in AI, Computer Science, or related fields; leadership experienceBachelor's or Master's in Data Science, Statistics, or related fields; technical skills
Work EnvironmentLeadership roles overseeing AI projects, strategic planning, cross-team collaborationData analysis, model development, statistical modeling, coding
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, e-commerce, research organizations

While both roles involve AI and data, the Generative Ai Director focuses on leading AI initiatives and strategic oversight, whereas the Data Scientist concentrates on data analysis and model development. The Director role typically requires more leadership experience and a broader understanding of AI applications.

What are the most commonly searched types of Generative Ai jobs in California?

The most popular types of Generative Ai jobs in California are:

What job categories do people searching Generative Ai Director jobs in California look for?

The top searched job categories for Generative Ai Director jobs in California are:

What cities in California are hiring for Generative Ai Director jobs?

Cities in California with the most Generative Ai Director job openings:

Infographic showing various Generative Ai Director job openings in California as of August 2026, with employment types broken down into 81% Full Time, 17% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Senior Director of Engineering, Generative AI

Roblox

San Mateo, CA • On-site

Full-time

Posted 12 days ago


Job description

Senior Director, Generative AI

About the Role

Roblox Build is our generative creation product, the platform where creators design, build, and publish 3D experiences. We are looking for a Senior Director of Generative AI to lead the Applied AI organization inside Build, responsible for turning state-of-the-art foundation models into high-quality, reliable creation systems at Roblox scale. This leader will own the full applied AI stack: model strategy and routing, model adaptation and fine-tuning, code generation (CodeGen), 3D layout generation (LayoutGen), and the evaluation science and infrastructure that tells us what actually works. 

You Will

  • Own model strategy and routing for Build. Design and build an intelligent model layer that selects the right model for each creation task based on quality, capability, latency, cost, and safety, leveraging both frontier models and Roblox-adapted open-source models.
  • Lead model adaptation across the Applied AI org, including fine-tuning, distillation, synthetic data generation, human feedback pipelines, and preference optimization for Roblox-specific creation tasks such as Luau code generation and 3D scene understanding.
  • Drive CodeGen capabilities forward by building AI systems that understand creator intent, reason across multi-file Roblox experiences, execute tools, and reliably make complex changes to existing games, going well beyond code completion.
  • Build LayoutGen intelligence by developing the AI capability that turns a creator's intent into coherent 3D scenes, including object selection, spatial reasoning, placement, aesthetic quality, and iterative editing.
  • Own evaluation as a core technical discipline. Build the benchmarks, quality metrics, judge methodologies, experiment infrastructure, and human evaluation pipelines that answer whether model, prompt, or routing changes actually improve creator outcomes.
  • Close the feedback loop between model development, evaluation, and production, ensuring that quality signal flows continuously from creator outcomes back into training data, model updates, and release decisions, rather than operating as separate silos.

You Have

  • 10+ years of experience in machine learning and AI, with 5+ years in senior technical leadership roles overseeing applied AI or ML engineering organizations that have shipped generative AI systems into production at scale.
  • Deep technical grounding across multiple areas of applied AI, including LLM post-training (RLHF, DPO, distillation), model routing and adaptation, agentic systems, code generation, or evaluation science, with enough depth to recruit, challenge, and lead exceptional scientists and engineers in each area.
  • Demonstrated experience building and leading high-performing organizations that span both AI research scientists and production engineers, including hiring, developing talent, and making difficult personnel decisions.
  • Strong evaluation fluency, with a track record of building eval frameworks that predict production outcomes, designing benchmarks that measure what matters, and building the infrastructure to run experiments continuously at model, prompt, and routing level.
  • Experience operating cross-functionally in complex technical organizations, with the ability to influence and align across research, product engineering, and platform teams without relying on hierarchy.
  • Genuine interest in the creation problem. You find the specific challenge of AI-assisted 3D world creation and domain-specific code generation compelling, not just as a vehicle for building AI systems.

You Are

  • A builder and a shipper who cares about getting things into production and measuring whether they actually work, not just publishing promising results.
  • Technically credible across the stack. You can engage deeply with scientists on evaluation methodology, data quality, and model behavior, and equally deeply with engineers on architecture, inference latency, and reliability.
  • Decisive under ambiguity. You make principled tradeoffs between rigor and velocity, know when good enough is good enough, and can articulate your reasoning clearly.
  • Direct and honest. You give clear feedback, surface problems early, and create an environment where your team can do the same.
  • Mission-driven. You care about the people building on Roblox, and you connect the technical work of the Applied AI org to the experience of the millions of creators using the tools.