Research Scientist - Autonomous Systems

Evolver; Palo Alto (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Evolver is seeking a Research Scientist specializing in autonomous systems, control, and optimization to develop methods that enable robust decision-making under uncertainty. You will translate mathematical theory into practical algorithms and prototypes, collaborating across research, engineering, and product teams.

Applicants with strong mathematical maturity, publication record, and a PhD or thesis-based Masters are encouraged, including exceptional recent graduates.

Qualifications

• Ph.D. or thesis-based Master’s in a quantitative field with thesis title and contributions described in application.
• Strong foundation in mathematical modeling and systems thinking.
• Research experience in dynamical systems/ control, optimization, stochastic systems, RL, or autonomous systems.

Responsibilities

• Develop methods for state and world modeling, estimation, planning, control, and sequential decision-making.
• Design approaches for autonomous systems under uncertainty and incomplete information.
• Develop adaptive planning and feedback mechanisms that update decisions as new information becomes available.
• Apply optimization, control, probabilistic reasoning, reinforcement learning to complex AI systems.
• Develop methods to evaluate robustness, reliability, and behavior of autonomous systems.
• Translate research into algorithms, prototypes, benchmarks, evaluation methods, and product architectures.
• Collaborate with research, engineering, and product teams to bring methodologies into real systems.

Skills

Autonomous systems

Control theory

Mathematical modeling

Optimization

Uncertainty decision-making

Python

Research communication

Education

Ph.D. or thesis-based Master in Electrical Engineering/Control/Robotics/Applied Math/OR/CS

Tools

Python

MATLAB

Job description

Evolver is an AI technology company transforming professional services. We combine deep domain expertise, advanced AI, and continuous applied learning to automate complex enterprise workflows while keeping people involved where judgment matters. Our goal is to help organizations operate more efficiently, accurately, and intelligently.

The Role

Evolver is looking for a Research Scientist with a strong background in autonomous systems, control, mathematical system theory, optimization, or decision-making under uncertainty.

You will help develop the methodologies underlying intelligent systems that perceive changing environments,maintainand update internal state, reason under uncertainty, plan and act,observeoutcomes, and adapt over time.

We welcome applications from exceptional recent graduates as well as experienced researchers. We care more about depth of thinking, mathematical maturity, and research ability than years of industry experience.

Experience in robotics or other physical autonomous systems is valuable, but this is not primarily a hardware or embedded-systems role.

What You'll Do

• Develop methods for state and world modeling, state estimation, planning, control, and sequential decision-making.
• Design approaches for autonomous systemsoperatingunder uncertainty and incomplete information.
• Develop adaptive planning and feedback mechanisms that update decisions asnew informationbecomes available.
• Apply optimization, control, probabilistic reasoning, reinforcement learning, or related methods to complex AI systems.
• Develop methods for evaluatingthe robustness, reliability, and behavior of autonomous systems.
• Translate research into algorithms, prototypes, benchmarks, evaluation methods, and product architectures.
• Collaborate with research, engineering, and product teams to bring new methodologies into real systems.

Minimum Qualifications

• Ph.D. orthesis-basedMaster's degree in Electrical Engineering, Control, Robotics, Applied Mathematics, Operations Research, Computer Science, Systems Engineering, or a related quantitative field(Note:Please include the title of your thesisin your applicationanda brief summaryof the problem, methodology, and your specific contribution).
• Strong foundationin mathematical modeling and systems thinking.
• Research experience in one or more of:
• dynamical systems and control
• optimization oroptimalcontrol
• stochastic systems
• reinforcement learning
• autonomous systems
• Strong Python or equivalent scientific computing skills.
• Ability to translate mathematical concepts into computational methods and working prototypes.

There is no minimum number of years of industry experience. Strong candidates maydemonstratetheir capabilities through a thesis, publications, research projects, internships, open-source work, or relevant industry experience.

Preferred Qualifications

• Research experience in areas such as model predictive control, stochastic control, POMDPs, Bayesian estimation, system identification, hybrid systems, multi-agent systems, or formal verification.
• Experience with robotics, autonomous vehicles, aerospace, industrial automation, or other complex autonomous systems.
• Strong publication record ordemonstratedresearch impact.
• Experience transferring research into production or real-world systems.
• Familiarity with modern machine learning, foundation models, or agentic AI systems.

Deep prior experience with LLMs, RAG, prompt engineering, or specific agent frameworks is notrequired.

Application

In your cover letter, please include the title of your thesis anda brief summaryof the problem,methodology, and your specific contribution.

About Evolver

Evolver is building intelligent enterprise systems that go beyond generating answers. Our systems must understand evolving situations, reason under uncertainty, make decisions, act, evaluate outcomes, and continuously improve.

We are looking for researchers who want to bring the foundations of systems, control, autonomy, and decision science into the next generation of AI.

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