About Applied Intuition
Applied Intuition is the vehicle intelligence company that accelerates the global adoption of safe, AI-driven machines. The company delivers the toolchain, Vehicle OS, and autonomy stacks to help customers build intelligent vehicles and shorten time to market.
Headquartered in Mountain View, CA, Applied Intuition has offices in multiple locations and serves the automotive, defense, trucking, construction, mining, and agriculture industries.
The Role
Decision Autonomy Engineer at Applied Intuition (via EpiSci, an Applied Intuition company) focuses on real-time decision-making, multi-agent coordination, and autonomous planning for battle management command and control (BMC2) and human-machine teaming across air, surface, and maritime domains.
You will help build intelligent agents that plan and execute missions using advanced reasoning, planning, and optimization algorithms, and you will work with cross-disciplinary teams to translate theoretical approaches into production-ready software.
Responsibilities
- Design and implement multi-agent optimization algorithms for distributed decision-making and coordination
- Develop temporal logic frameworks and constraint-satisfaction algorithms for complex planning scenarios
- Create mathematical models for sequential decision processes under uncertainty with probabilistic outcomes
- Build computational frameworks that balance algorithmic efficiency with human-interpretable reasoning
- Implement and evaluate quantitative metrics for algorithm performance, solution quality, and computational efficiency
- Translate theoretical approaches into production-ready software with rigorous testing methodologies
- Collaborate with cross-disciplinary teams to refine algorithmic approaches based on empirical evaluation
- Communicate technical details effectively across stakeholders, sponsors, and leadership
Qualifications
- MS or PhD in Computer Science, Robotics, Optimization, Decision Science, or related field, OR 3+ years of experience developing intelligent agent or planning systems
- Strong theoretical understanding of algorithmic complexity, graph theory, information theory, and optimization techniques
- Experience implementing algorithms for constraint satisfaction problems, scheduling, or path planning
- Proficiency with modern programming languages (C++, Python) and development environments
- Ability to analyze and visualize algorithm performance and solution quality
- Ability to translate complex mathematical concepts into clear technical documentation
- Strong critical thinking and methodical approach to algorithm development and validation
- Ability to work independently and thrive in a dynamic, fast-paced environment
Travel Requirements
- Occasional travel required (approximately 10–20%) for demonstrations, integration, or customer engagement
- This role can be based in Washington, DC; Mountain View, CA; San Diego, CA; Ann Arbor, MI; or Fort Walton Beach, FL. Candidates from other U.S. locations may be considered if willing to travel or relocate
Security Requirements
- Must be a U.S. citizen
- Must be eligible for a U.S. SECRET clearance with SAP eligibility
For more information about U.S. security clearances: click here.
Compensation
Base salary range for this role is $155,000 to $190,000 USD annually, with the total compensation package including equity and benefits. Actual offers depend on experience, credentials, and other factors. Benefits include health, dental, vision, life and disability insurance, 401k with employer match, and paid time off. Note that benefits are subject to change and may vary by jurisdiction.
Location and Seniority
- Seniority level: Mid-Senior level
- Employment type: Full-time
- Job function: Engineering and Information Technology
- Industries: Software Development
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