C++ Multi-Agent Autonomy Engineer - Clearance Eligible - Remote
Decisive Point
Location: Remote
Time: 2 weeks ago
Responsibilities
-
- Work as part of a team to design multi-agent, multi-domain autonomy algorithms in the fields of Optimization, Persistent Search, and Coordinated Behaviors for a diverse set of defense problems.
- Work with an awesome team of engineers as you contribute to a quickly growing multi-domain tactical autonomy group in support of the US Navy Warfighter.
- Develop modular agile autonomy applicable to a diverse set of problems.
- Support field testing and evaluation exercises several times a year with different USV and UAV platforms.
- Implement, leverage and improve state-of-the-art unmanned aerial system (UAS) multi-agent autonomy algorithms in C++ tactical military missions within the following paradigms:
- Autonomy loops such as: “Sense, Make Sense, Decide, Act (SMDA)”, “Observe, Orient, Decide, Act (OODA)” loops., “Perceive, Decide, Act’ (PDA)” loops.
- Sense: Environment sensing and modeling, computer vision, sensor processing, classification, anomaly detection.
- Make Sense: Environment mapping, data interpretation, 3D voxel grids, GeoGrids, WGS84, aerospace coordinate systems and reference frames (north east down (NED), Geocentri & Geodetic latitudes, Earth-centered-inertial (ECI), earth centered earth fixed (ECEF)), no fly zones, keep-in/keep-out zones. Sensor fusion and target tracking, etc. Find, fix, track, target (F2T2).
- Decide: State machines, behavior trees, optimization algorithms, constraint solving, classic algorithms (A*, RRT*, DFS, BFS, Branch & Bound, Random Forests), heuristics, optimization, Kalman filters, particle filters, etc. Artificial intelligence techniques such as deep reinforcement learning, reinforcement learning, machine learning, neural networks, supervised learning, unsupervised learning, generic algorithms, Bayesian networks, fuzzy logic, etc.
- Act: Autonomous 2D & 3D UAS trajectory/motion planning, route planning, SLAM. Classical controls systems, optimal control systems, adaptive control systems, model predictive control systems, especially for integration of 3rd party UAS autopilots. Guidance, navigation, and controls (GNC).
- Build, leverage, and improve C++robotic autonomy software architectures that can be deployed on real systems to accomplish military missions (including publish/subscribe architectures).
- Design C++ autonomy tracking and fusion software in collaboration with autonomy engineers that supports full integration with aircraft autopilots, datalinks, sensors, PNT/GPS/INS, ground control stations, etc.
- Support live flight test of autonomy software on F16s, group 1-5 unmanned aerial vehicles (UAVs).
- Collaborate with 3rd party UAS vehicle vendors on the integration of EpiSci autonomy software onto OEM UAS hardware.
- Collaborate with domain experts and prior DoD warfighters (ex. DoD fighter pilots) to build software autonomy solutions for military missions.
Minimum Qualifications
-
- Education Requirements:
- MS or PhD degree in Robotic Engineering, Computer Science, Computer Engineering, Optimization, or related engineering field.
- 5+ years of relevant experience designing multi-agent autonomy.
- Technical Requirements:
- Experience with Swarm Optimization or Multi-agent Systems and Optimization.
- Understanding of behavior logic frameworks (state machines, behavior trees, hierarchical task networks).
- Proficiency in Python and Linux.
- Understanding of modern C++ and willingness to develop in it.
- Experience developing in Docker and containerized development environments, and using Linux-based operating systems (e.g., RHEL, Ubuntu).
- Experience using git, Visual Studio Code, GitLab, Nexus, SonarQube, Azure Container registry.
- Additional Requirements:
- Passion for solving complex problems with little supervision in a fast-moving team.
- 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.
- Travel Requirements
- Must be willing to travel as projects requires. Estimated travel average is 25%. If you live in Sothern California, there will be less travel.
- Security Requirements
- (MANDATORY) Must be a U.S. Citizen.
- (MANDATORY) Must be eligible for a U.S. SECRET security clearance.
Preferred Qualifications
-
- Education Requirements:
- MS or PhD degree in Robotic Engineering, Computer Science, Computer Engineering, Optimization, or related engineering field.
- 7+ years of hands-on experience developing modern C++ tracking and fusion software for autonomous robotic systems.
- Technical Requirements:
- Research in multi-agent coordination algorithms.
- Understanding of Multi-Agent Algorithms (e.g., Ant-Colony Optimization, Swarm Particle Optimization, Stigmergy, and Wolf Pack Algorithm).
- Experience with Multi-Agent Deep learning using Pytorch or Tensorflow.
- Proficiency in modern C++.
- Familiarity with software-in-the-loop (SIL) and hardware-in-the-loop (HIL) development and testing.
- Experience working projects related to national security for one or more government agencies.
- Interdisciplinary background, with evidence of continual learning.
- Python experience.
- Security Requirements
- (MANDATORY) Must be eligible for a U.S. SECRET security clearance.
EpiSci is proud to be an equal opportunity and affirmative action employer. We are committed to equal employment opportunity regardless of race, color, religion, sex, sexual orientation, age, marital status, disability, gender identity or Veteran status. We value our differences and we’re excited to learn what you can add to our team.
Don't meet every single requirement? At EpiSci, we're committed to building a diverse, inclusive, and authentic workforce, so if you're excited about this role but your previous experience doesn't align perfectly with every qualification, we encourage you to apply anyway! You may be the perfect candidate for this or another role at EpiSci.
