Outerport
Steady
Automate design checks, process calculations, bill-of-material validations, design-for-manufacturing analysis, and other engineering workflows across drawings, CAD files, and datasheets.
- Open roles
- 6
- New role every
- ~30.0 days
Company signals
Score: 65
GitHub org
Yes
Missing required salary
0%
New cities (90d)
3
Stale listings
0%
Wide pay-band rate
33%
Buzzword-heavy listings
50%
GitHub stars
14
Role diversity (90d)
0 distinct titles
Job facts
- Location
- San Francisco, California, United States of America
- Type
- Full-time
- Salary
- $100K – $200K
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Member of Technical Staff, Reinforcement Learning
at Outerport
We’re looking for candidates with experience building reinforcement learning- based LLM training pipelines.
As part of our founding team you may:
- Train reinforcement learning-based LLMs to solve tasks in the domain of materials science, chemical engineering, and engineering science
- Integrate simulation tools and real hardware to collect data
- Work with and source data from vendors
- Evaluate, test, and deploy models
Qualifications (none of these are hard requirements)
- Industry experience or projects working on hard problems in machine learning (with Python / PyTorch)
- Being scrappy (getting things done, over theoretical soundness)
- Publication record in venues like ICLR, NeurIPS, ICML, and others
- Good visual taste / an appreciation for aesthetics
- A reputation for having an “engineering mindset”
- Strong communication skills
- Experience working with various engineering simulation tools (e.g. CAE, EDA tools)
- Interest in manufacturing, engineering, EPC, semiconductors, materials science