Software Engineer - On-board Autonomy (II)
Lodestar · Los Angeles, US
Posted about 3 months ago · $115,000 - $174,000
or apply directly on Lodestar's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 81 days Lodestar's roles stay open a median of 57 days
- Reposted
- No
- Salary listed
- Yes 58% of Lodestar's roles list one
- Ghost-job risk at Lodestar
- high 9 stale, 2 reposted of 12 open
- Hiring momentum
- 14 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-10-24
Measured from postings appearing on and disappearing from Lodestar's own greenhouse board since 2026-08-03. Full hiring picture for Lodestar.
About this role
As a Software Engineer II - On-board Autonomy at Lodestar, you will develop decision-making systems for the company's AI-enabled autonomy software suite, MITHRIL. Your role involves creating algorithms for real-time autonomous decision-making, integrating various models to ensure spacecraft can operate effectively in complex environments. You will also work on building and maintaining the necessary infrastructure for testing and deploying these systems in space missions.
- benefits
- 3/5
- freshness
- 1/5
- career value
- 4/5
- role clarity
- 4/5
- pay transparency
- 5/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Lodestar as an employer.
What you need
- 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
Nice to have
- 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)
What you get
- Pay Range: (P2) Developing: $115,000 - $174,000 / year; (P3) Career: $136,000 - $200,000 / year
- 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
Worth weighing
- No specific mention of remote work options or hybrid work policies
- Compensation bands vary based on individual qualifications and experience, which may lead to variability in offers
- The role requires compliance with ITAR regulations, limiting applicants to U.S. citizens or lawful permanent residents
Summarised from Lodestar's posting. Read the full original.
Listed by Lodestar on their greenhouse job board, last confirmed open on 2026-10-24. PitchMeAI is not the employer.
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