Company Overview
Foundational is building a network of AI-native, autonomous factories for modern contract manufacturing. We’re reshoring critical supply chains so companies can produce high‑quality products domestically, quickly, and at competitive cost.
Foundational exists to make reindustrialization practical. Our factories are autonomy-first, reconfigurable by design, and orchestrated by a unified, AI-native factory operating layer that connects design through production.
Transformative Opportunity
Recent breakthroughs in robotics and physical AI have shifted autonomous manufacturing from a theoretical promise to a deployable capability, triggering a global race to operationalize these systems at scale. The challenge is no longer whether autonomy works, but who can integrate AI-native robotics into real production environments.
The ability to manufacture advanced products domestically is now central to U.S. economic competitiveness and national security. Foundational is focused on deploying these capabilities at scale during a decisive decade for American industrial leadership.
Who We Are
Foundational was built by executive leadership from Google’s physical AI platform and America’s two largest contract manufacturers.
Manufacturing critical products requires trust. The Foundational team has deployed AI systems at multi-billion-dollar scale and delivered thousands of products across hundreds of manufacturing facilities.
Role Overview
We are hiring a Head of AI Manufacturing to own the design, development, and deployment of AI systems across Foundational’s manufacturing platforms. This role is responsible for defining how machine learning and data-driven systems are applied in production environments to improve quality, throughput, reliability, and scalability.
This role requires both technical leadership and hands-on execution. You will set the AI architecture and standards while working directly with software, controls, and manufacturing teams to integrate AI into real-world factory systems. You will ensure AI capabilities are production-ready, secure, and deliver measurable operational impact as our factories scale.
Key Responsibilities
• Define and lead Foundational’s AI strategy for manufacturing, aligning machine learning and data systems with operational goals across automation, quality, throughput, and cost.
• Architect and deploy full-stack AI systems spanning data ingestion, feature pipelines, model training, deployment, monitoring, and feedback loops in production environments.
• Develop and integrate AI-driven capabilities such as perception, anomaly detection, predictive analytics, optimization, and decision support into manufacturing and automation systems.
• Partner closely with software, controls, robotics, and manufacturing engineering teams to integrate AI models into real-time, production-ready systems.
• Lead experimentation and proof-of-concept efforts to evaluate new AI approaches and rapidly translate successful prototypes into deployed systems.
• Establish standards for reliability, security, monitoring, and lifecycle management of AI systems operating in mission-critical manufacturing environments.
• Build, mentor, and lead a team of AI engineers and applied data scientists, setting technical direction while remaining engaged in system design and problem-solving.
• Stay current on advances in AI and machine learning and assess their practical applicability to Foundational’s manufacturing platforms and long-term roadmap.
What You’ll Bring
• 8+ years of experience in AI, machine learning, or applied data systems leadership, including technical ownership of production AI systems.
• Deep hands-on experience designing and deploying full-stack AI solutions, including data pipelines, model development, deployment, and monitoring.
• Strong applied background in machine learning domains relevant to manufacturing, such as computer vision, time-series analysis, optimization, or predictive modeling.
• Proven experience integrating AI systems into production software, automation, or industrial platforms with real-world reliability, latency, and safety constraints.
• Fluency with modern software and infrastructure stacks for AI deployment, including cloud platforms, containerization, and MLOps workflows.
• Strong cross-functional leadership skills, with experience working closely with software, hardware, and operations teams to deliver end-to-end systems.
• Deep alignment with Foundational’s mission to reindustrialize the United States, motivated by long-term impact, ownership, and building enduring platforms.
Why Join Foundational
Foundational is built for people who want their work to matter. The ability to manufacture critical products domestically is central to U.S. economic strength and national security, and we are focused on turning that imperative into execution at scale.
We operate with a strong bias toward delivery. Progress is measured by what runs in production, what holds up under pressure, and what improves over time. Ownership, judgment, and follow-through define our culture.
Foundational brings together the most experienced leadership team in autonomous manufacturing — operators who have run the largest contract manufacturing platforms in the United States, alongside engineers who have built and deployed large-scale systems at Google. This combination positions us as the clear leader in this category, with both the credibility and capability to set the standard for autonomous production.
We reward exceptional outcomes exceptionally. Compensation and equity are structured to reflect responsibility, impact, and results, with meaningful upside for those who help build and scale the business. For those aligned with the mission and motivated by execution at scale, Foundational offers the opportunity to help define one of the most consequential industrial transformations of the next decade.
If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.
Senior AI Engineer / AI Technical Architect sought by a top-ranked hospital to design and operationalize cloud-based AI/ML solutions using Epic and Azure to improve clinical and operational outcomes.
Lead language-focused research and large-scale analyses at Slingshot AI to develop scientifically rigorous, product-relevant metrics that improve mental health outcomes.
Lead applied ML and LLM initiatives at Gametime to design, deploy, and iterate ranking, personalization, and semantic models that drive measurable product and business outcomes.
Work on recommendation, multi-modal embeddings, and generative models to improve dating outcomes at Hinge by taking research-grade ML into production for millions of users.
Lead the design and implementation of LLM-powered clinical agents, multi-agent orchestration, and retrieval systems to enable autonomous, multi-step clinical reasoning.
Join Mirage's NYC product team as a Product Data Scientist to lead experimentation, define core metrics, and turn analytics into product decisions that move the needle.
Lead the design and production of generative AI coaching systems at BetterUp, shaping product direction while mentoring engineers and partnering across product, design, and research.
Lead the development of a production-ready, multi-asset optimization and real-time bidding platform to enable automated ERCOT market decisions at scale for Intersect.
Lead R2Net's data science function to turn rich data assets into operational models, scalable experimentation, and clear business-facing analytics that improve pricing, forecasting, assortment, and customer experience.
Mirage, a leading AI short-form video company based in NYC, is hiring a Marketing Data Scientist to build measurement foundations, improve acquisition performance, and inform go-to-market strategy.
TMEIC is hiring an AI/ML Applications intern to help design, build, and deploy data analytics, visualizations, and machine learning solutions for its Energy and Infrastructure business.
Work on Notion’s Growth team to design experiments, build metrics and predictive models, and turn quantitative insights into product and revenue impact.
Contribute to production-ready machine learning and analytics at Spring Venture Group as a Junior Data Scientist, applying Python, SQL, and modern AI tools to improve KPIs and automate workflows.