Software Engineer: On-board Autonomy
Moore Information Inc
2 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
Junior Compensation
$ 180KJob location
Tech stack
Amazon Web Services (AWS)
Azure
C++
Cloud Computing
Communications Protocols
Continuous Integration
Linux
Distributed Computing Environment
Python
Machine Learning
Performance Tuning
TensorFlow
Reinforcement Learning
Multithreading
Real Time Systems
PyTorch
Delivery Pipeline
Multi-Agent Systems
GIT
Containerization
Information Technology
Docker
Job description
- Design and implement on-board decision-making models that recommend and adapt strategies in real time
- Develop autonomous decision algorithms that integrate information from perception, state estimation, and intent prediction models to execute mission objectives
- Research and implement ML models for decision making - everything from lit. review, through training, to deployment
- Implement decision models that adapt dynamically to changing mission context, environmental conditions, and system status
- Develop frameworks for continuous re-evaluation of active strategies to ensure resilient and adaptive behavior under uncertainty
- Support real-time autonomy in communications-limited or time-critical scenarios
- Build and maintain autonomy infrastructure, testing frameworks, and deployment pipelines for space missions
Requirements
Do you have a Master's degree?, * Bachelor's or Master's degree in Computer Science, Machine Learning, Robotics, a related field, or equivalent experience
- 2+ years of distinguished industry experience in autonomy, decision-making, or control systems for aerospace/robotics
- Strong proficiency in C++ and Python and DL frameworks (PyTorch, TensorFlow)
- Demonstrated experience with machine learning applied to decision-making or control problems
- Track record with optimal control, planning, or reinforcement learning in real-time systems
- Familiarity with multi-agent decision-making or planning under uncertainty, * Track record implementing autonomy applications in real-time or safety-critical environments
- Experience integrating perception and prediction outputs into decision frameworks
- Familiarity with resource-aware strategy selection and optimization under uncertainty
- Background in reinforcement learning, hierarchical planning, or adaptive control
- Experience with distributed training and cloud-based scaling of ML models (AWS, GCP, or Azure)
- Experience with Linux, Git, and CI/CD pipelines
- Comfortable with containerization tools such as Docker and Kubernetes
- Familiarity with real-time systems, multi-threading, and performance optimization
- Strong understanding of distributed autonomy, networking, and communication protocols
Benefits & conditions
Pulled from the full job description
- 401(k)
- Health insurance
- 401(k) matching
- Paid time off
- Vision insurance
- Dental insurance
- Stock options, * Pay Range:
- (E1) Junior Software Engineer: $120,000 - $145,000 / year
- (E2) Software Engineer: $140,000 - $180,000 / year
- (E3) Senior Software Engineer: Competitive
- Meaningful equity incentives as part of our employee option pool
- Flexible PTO with generous paid vacation, holidays, and sick leave
- Comprehensive medical, dental & vision coverage
- 401(k) retirement plan with company match
- LA, Compensation bands are determined by role, level, location, and alignment with market data. Individual level and base pay is determined on a case-by-case basis and may vary based on job-related skills, education, experience, technical capabilities and internal equity. In addition to base salary, for full-time hires, you may also be eligible for long-term incentives, in the form of stock options , and access to medical, vision and dental coverage, as well as access to a 401(k) retirement plan.