AI Control Theory & Optimization Scientist
Do you dream of working with cutting-edge technology for a category-defining product? PassiveLogic is looking for a highly motivated and dedicated candidate who wants to learn from the best and stretch their skills in our multiple applications.
About PassiveLogic
PassiveLogic is the first fully autonomous platform for buildings. We’ve reinvented the fundamental principles of automation to democratize technology, optimize buildings, and reduce the world’s carbon footprint. We are a team of technologists, engineers, and creatives dedicated to making a sustainable impact through real-world solutions.
We are looking for team members who have a passion for technology and want to work on cutting-edge problems with real-world solutions. Our culture is built on bringing together the most talented engineers, thinkers, and creatives — backed by the world’s leading investors — working together to make the future a reality.
About the Role
This is a career-defining opportunity to play a crucial role in a hyper-scale AI company that is transforming the future of autonomous systems, energy, and the built environment.
The AI Control Theory & Optimization Scientist plays a key role in the Digital Twins team designing and developing scalable solutions using gradient control theory methods.
What you’ll do
- Develop predictive models: Develop predictive models leveraging deep learning, reinforcement learning, and transfer learning techniques.
- Create autonomous agents: Develop autonomous agents for generative training of deep learning predicates.
- Develop advanced algorithms: Develop algorithms such as stochastic gradient descent, coordinate descent, distributed optimization, Bayesian methods, and evolutionary algorithms.
- Utilize big data: Utilize big data computation and storage models to create prototypes and data sets.
- Optimize model workflows: Conduct model training, evaluation, integration, testing, and optimization to deliver high-performing solutions.
- Expertise in AI tools: Act as a subject-matter expert in TensorFlow, PyTorch, Halide, and other AI tools.
What you’ll bring
If your experience does not meet all our posted requirements below, we’d still love to hear from you. We are looking for practitioners who are passionate about understanding people, committed to lifelong learning, and driven by the love of what they do. If that’s you, please apply!
You must have
- Proven Experience:
- MS or PhD in Control Engineering, Computer Science, Mathematics, or related fields.
- Demonstrated expertise in AI development, scientific machine learning, reinforcement learning, multiagent systems, and optimization.
- Strong background in model predictive control and programming skills (e.g., Swift, C++, Python).
- Exceptional Communication Skills: Excellent interpersonal skills and a team-oriented mindset.
- Organized and Strategic: Strong analytical and problem-solving skills, particularly in mathematics and numerical methods.
- Collaborative Mindset: Open to feedback and committed to a continuous improvement process.
- Adaptability: Comfortable in a fast-paced startup environment, eager to learn, iterate, and innovate.
- Problem solving: You own this role. When issues arise, be the empowered force that solves them, rolling-up.
You should have
- Automatic differentiation expertise: Experience with automatic differentiation and differentiable programming.
- Software design skills: Experience with software design, design patterns, and software architecture.
- Systems modeling and algorithms: Experience with systems modeling and algorithm development.
It’s helpful to have
- Graph neural network expertise: Experience in building and training graph neural networks.
- Swift development skills: Practical experience with the Swift programming language.
- Computational methods proficiency: Experience in vector, SIMD, and tensor computational methods.
- Startup experience: Background in fast-paced startup environments.
- Autonomous systems knowledge: Hands-on experience designing, simulating, or deploying autonomous systems.
We know there are candidates who might not fit everything we’ve described above, or who might have experience and skills we haven’t considered. PassiveLogic can sometimes be flexible enough to shift responsibilities to the right person, or otherwise identify open or upcoming roles that may better fit your professional background. Even if you don’t meet all the requirements above, we still want to hear from you.
Compensation, Benefits & Perks:
- Competitive compensation
- Generous equity share package
- Medical, dental and vision coverage
- Disability and Life Insurance options
- Flex PTO
- Team building events
- Free catered lunch in the office Monday — Friday
- Free ski pass (We are at the base of Big Cottonwood Canyon)
- Free National Park pass
When applying, include:
- A cover letter telling us why you're the perfect candidate for PassiveLogic
- A resume
- Extra mile — include a description of a project (of any type) you personally created, devised, built, managed, organized, or designed that was of your own self-initiative
Diversity and inclusion
Diversity, inclusion, and belonging is woven into our values and everything we do. We welcome all — come as you are and bring your whole self. We are proud to be an Equal Opportunity Employer. We celebrate diversity every day by maintaining a safe and inclusive environment for our employees at every stage of their careers.
- Department
- Software Engineering
- Role
- Quantum & Digital Twins
- Locations
- Salt Lake City
About PassiveLogic
PassiveLogic enables autonomy for controlled systems and unlocks collaboration between teams to manage those systems. PassiveLogic has reimagined how we design, build, operate, maintain, and manage infrastructural robots, whose current technology has remained unchanged for decades. By using revolutionary physics-based Quantum digital twins and leveraging the world’s fastest AI compiler to simulate future-forward controls, PassiveLogic empowers users to easily create their own generative digital twins in minutes to launch autonomous control. This control optimizes for energy use, equipment longevity, and occupant comfort levels in real time for the system’s lifetime. Autonomous control lays the foundation for decarbonization at scale and enables truly smart, connected cities. PassiveLogic is backed by leading investors including nVentures, Era Ventures, Keyframe Capital, Addition, RET Ventures, noa (formerly A/O Proptech), and Brookfield Growth.
AI Control Theory & Optimization Scientist
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