EpiSci · 2 days ago
Multi-Agent Teaming Autonomy Engineer - Clearance Eligible - (Remote)
Maximize your interview chances
AerospaceArtificial Intelligence (AI)
No H1BU.S. Citizen OnlySecurity Clearance Required
Insider Connection @EpiSci
Get 3x more responses when you reach out via email instead of LinkedIn.
Responsibilities
Build decision making architectures for coordination of actions across teams of homogeneous or heterogeneous autonomous agents.
Build autonomous products that operate in real world environments with limited human interaction
Develop and implement techniques to promote explainability within the decision-making architecture
Write software that operates real autonomous aircraft systems including F16 fighter jets, group 1-5 unmanned aerial vehicles (UAVs), as well as simulated models to accomplish tactical military missions
Implement, leverage and improve state-of-the-art decision-making technology for unmanned aerial systems (UAS) that to perform tactical military missions using common autonomy loops:
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)
Collaborate with autonomy engineers to implement production level software for autonomous UASs
Build, leverage, and improve robotic autonomy software architectures that can be deployed on real systems to accomplish military missions (including publish/subscribe architectures).
Design autonomy 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 military aircraft such as 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
Qualification
Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.
Required
Bachelor’s degree in computer science/related engineering field
5+ years of hands-on experience developing multi-agent teaming software for autonomous robotic systems
Experience with C++/Python Autonomy algorithms
Experience in one or more of the following: State Machines, Behavior Trees, Resource Allocation, Task Planning, Machine Learning, Multi Agent Reinforcement Learning
Experience developing decision making AI for autonomous unmanned systems
Experience with Python
Strong procedural and object-oriented programming experience that employs clean code principles and good OOP design patterns/principles.
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
Experience working with best-effort communication systems, serialization, message schema development, and state synchronization
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
Must be willing to travel as projects require. Estimated average travel is once every other month for between 2 days up to 1 week. (:20%)
Must be a U.S. Citizen
Must be eligible for a U.S. SECRET security clearance with Special Access Program Eligibility
Preferred
Master’s degree in computer science/related engineering field
8+ years of experience developing multi-agent teaming software for autonomous robotic systems
Experience with 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
An active U.S. SECRET security clearance with Special Access Program Eligibility
Benefits
Equity
Sign-on payments
Full range of medical, financial, and/or other benefits
Company
EpiSci
EpiSci develops Tactical AI based trusted, hardware-agnostic, and rapidly portable autonomy solutions for unmanned/uncrewed UxV platforms.
Funding
Current Stage
Growth StageTotal Funding
unknown2024-06-13Acquired· by Merlin Labs
2023-04-20Seed· Undisclosed
Recent News
Washington Technology
2024-05-23
Company data provided by crunchbase