We are an in-office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments.
As a Collaborative Autonomy Engineer on the Cross Domain Autonomy team, you will be pivotal in developing and testing collaborative autonomy behaviors for large teams of heterogenous autonomous vehicles, across different domains (e.g., surface, air), with different sensor suites (e.g., camera, radar) that work together to accomplish complex mission vignettes. Your team will continuously add capability and demonstrate the solution to customers in real-world scenarios on a variety of HW platforms. Your responsibility will primarily be designing and developing multi-agent multi-domain behavioral autonomy algorithms, but you will work with the team to make the entire system successful.
- Adapt and develop cutting edge, modular, and agile autonomy capabilities in the fields of optimization, persistent search, and coordinated behaviors, applicable to a diverse set of Defense problems
- Integrate tactical autonomy solutions onto hardware platforms, interface sensors, and test and validate autonomous behaviors, including on-site demonstrations for software field testing and evaluation exercises with the US Navy
- Design, test, and ultimately implement software within a component-based architecture, including occasionally integrating externally developed software capabilities into the system
- Deploy containerized autonomy solutions to embedded Linux devices, leveraging computer-in-the-loop testing and profiling, and efficiently collecting performance data
- Troubleshoot and debug complex issues related to behavioral autonomy and system performance, ensuring robust and reliable operation
- Contribute novel engineering ideas, algorithms and concepts for new and existing research and development projects
- Collaborate with cross-functional teams, domain experts, prior DoD warfighters, and program managers to build software solutions for military missions
- Effectively communicate solutions to a diverse team of engineers, program managers, executives, and sponsors
- MS or PhD in Robotic Engineering, Computer Science, Computer Engineering, Optimization, or equivalent OR 5 years of relevant experience designing multi-agent autonomy
- Understanding of Multi-Agent Algorithms including Ant-Colony Optimization, Swarm Particle Optimization, Stigmergy, and Wolf Pack Algorithm
- Experience with Swarm or Multi-agent Systems and Optimization
- Quality assurance testing of robotic software (metric development, test and evaluation, validation and verification of software)
- Deep understanding of behavior logic frameworks (state machines, behavior trees, hierarchical task networks)
- Experience with modern C++ development (2011, 2017, 2020, smart pointers, etc.), CMAKE, Python and Bash
- Comfortable in both Windows, Linux, and Docker
- Prior experience with remote software development, ability to handle and process large datasets, and learn new software and algorithms as needed with little supervision
- Must be willing to travel as projects requires, usually for SW/HW integration and/or demonstrations; estimated average travel is every 1-2 months for 2-5 days (10-20%)
- Travel-adverse candidates are encouraged to inquire about relocation assistance to HQ in Poway, CA
- Must be a U.S. Citizen
- Must hold or be eligible to obtain and maintain a U.S. security clearance
For more information about U.S. security clearances: click here.
Nice to have:- Passion for solving complex problems with little supervision in a fast-paced environment
- Ability to balance multiple priorities in a fast-paced, highly collaborative, frequently changing, and sometimes ambiguous environment
- Excellent analytical, communication, and documentation skills with demonstrated ability to collaborate across multiple teams
- PhD in computer science or engineering (electrical & computer, systems and industrial, mechanical, etc.)
- Expertise in machine learning techniques, including supervised and unsupervised learning Preferred that candidate is also experienced with deep learning and neural architectures, such as CNNs, RNNs, GANs, and transformers
- Proficiency in C++, Python (including TensorFlow and Py torch), and Bash
- Experience with robotics SDKs, such as ROS2
- Experience with Docker
- Experience with Agile development methodologies and familiarity with CI/CD best practices.
- Experience working with edge computing and real-time systems
- Integration and test experience on common COTS hardware devices (e.g., Nvidia Jetson, Xilinx RF/MPSOC)
- Interdisciplinary background, with evidence of continual learning
- Current U.S. SECRET security clearance
Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment.
Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position.
Please reference the job posting subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the location listed is: $125,000 to $185,000 USD annually.
Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.
Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60-1.4(a), 41 CFR 60-300.5(a) and 41 CFR 60-741.5(a) and that these laws are incorporated herein by reference. These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. These regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws.
Top Skills
What We Do
As the foremost enabler of autonomous vehicle development, Applied Intuition equips engineering and product teams with software that makes it faster, safer, and easier to bring autonomy to market.
Applied’s suite of products, focused on simulation and analytics, delivers sophisticated infrastructure built for scale. Companies of all sizes use Applied to comprehensively test and rapidly accelerate their autonomous vehicle development.
Headquartered in Silicon Valley with offices in Detroit, Tokyo, and Munich, Applied is composed of software and automotive experts from the top companies in the world (such as Google, Amazon, Apple, Waymo, Tesla, Delphi, GM, and Bosch).
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