CTO at Morio AI
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Experience Required:
Posted on:
2 hours ago
Vacancies:
1 Vacancy
Job Summary
This is a remote position.
What is allUP Morio AI has partnered with allUP to help streamline their hiring process. allUP is a new professional network and recruiting firm built around casual videos that will make it easier for Morio AI to get to know you beyond just a resume.
About our client: Morio AI is stealth-stage AI venture is emerging from a global leader in energy and industrial innovation. Backed by a committed corporate anchor investor and operating at the intersection of AI chemistry and decarbonization the company is building a category-defining platform to accelerate compound discovery and optimization starting with critical challenges in energy and emissions.
This is not an idea-stage startup. The venture has a validated technical foundation and a paid commercial pilot with a Fortune 500 energy partner.
This is not an idea-stage startup. The venture has a validated technical foundation and a paid commercial pilot with a Fortune 500 energy partner.
About the Role: As CTO this person will own the end-to-end technical vision for Morio: from AI architecture to lab automation. They will take the helm of a platform already showing breakthrough results in CO₂ capturenow ready to scale. They will guide the convergence of ML computational chemistry and robotic workflows leading a world-class team to build the industrys first closed-loop discovery engine for advanced materials.
They will work closely with the CEO and Chief Scientist to translate research breakthroughs into scalable defensible productsand set the technical culture for a high-performance team operating at the intersection of science and engineering. This is a founder-track role with significant equity and the opportunity to define the category of autonomous science platforms.
What Youll Do
- Architect the Platform: Own the design and build out of the AI-powered discovery engine and robotic lab infrastructure.
- Lead Engineering & ML: Direct teams across data engineering ML simulation and lab automation to integrate physical and digital discovery loops.
- Productize Science: Translate cutting-edge research into scalable APIs pipelines and tools.
- Own IP & Infrastructure: Ensure defensibility via software models data and system architecture.
- Build the Team: Recruit and mentor top-tier technical talent across ML software automation and data science.
- Partner Closely with Science: Collaborate with the Chief Scientist and domain experts to bridge chemistry and compute.
- Scale Systems: Design for reproducibility experiment tracking and high-throughput discovery workflows.
Requirements
What Theyre Looking For
- Track record of leading 01 product development in AI/ML scientific computing or robotics
- Experience deploying cloud infrastructure for scientific workflows (e.g. AWS Azure GCP on-prem/hybrid)
- Technical fluency across ML generative models computational chemistry or lab systems
- Strong instincts for building scalable architecture balancing rigor with speed
- Familiarity with GNNs diffusion models active learning or reinforcement learning in physical contexts
- IP experience (software patents defensible system architecture etc.)
What Sets You Apart
- Systems Thinker: Sees end-to-endfrom lab hardware to ML ops to customer value
- Builders Mindset: Hands-on yet capable of setting technical strategy and scaling teams
- Deep-Tech Operator: Knows what it takes to move from research prototype to product deployment
- Customer-Oriented Technologist: Understands how technology enables real-world industrial impact
- Collaborative Leader: Thrives at the intersection of science engineering and commercial execution
Benefits
Why This Role Matters: They are building a system to compress 1020 year R&D cycles into 12 years. The technical architecture this person builds will define not just the success of the venturebut the blueprint for how industrial science gets done in the AI era.
Compensation
Base: $230260k
Bonus: 1015%
Significant Equity
Significant Equity
Required Skills:
- Track record of leading 01 product development in AI/ML scientific computing or robotics - Experience deploying cloud infrastructure for scientific workflows (e.g. AWS Azure GCP on-prem/hybrid) - Technical fluency across ML generative models computational chemistry or lab systems - Strong instincts for building scalable architecture balancing rigor with speed - Familiarity with GNNs diffusion models active learning or reinforcement learning in physical contexts - IP experience (software patents defensible system architecture etc.)
Company Industry
IT Services and IT Consulting
Key Skills
- Risk Management
- Conflict Resolution
- Incident Reports
- Justices
- Legislative Process
- Emergency
- Rescue Operations
- safety compliance
- Professional Development
- Access Control
- Personnel Management
- Safety Management
- Risk Assessments
- General Public
- Social Events
