or apply directly on Atomic Machines's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 29 days Atomic Machines's roles stay open a median of 45 days
- Reposted
- No
- Salary listed
- No 0% of Atomic Machines's roles list one
- Ghost-job risk at Atomic Machines
- high 17 stale, 3 reposted of 27 open
- Hiring momentum
- 43 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-09-17
Measured from postings appearing on and disappearing from Atomic Machines's own greenhouse board since 2026-08-03. Full hiring picture for Atomic Machines.
About this role
In this role, you will develop software capabilities for Design for Manufacturing (DFM) within Atomic Machines' Matter Compiler technology. Your responsibilities include creating algorithms that convert device geometry into manufacturable geometry, encoding manufacturability constraints, and collaborating with cross-functional teams to ensure designs are feasible. You will also validate designs against real-world manufacturing processes and maintain a knowledge base of production history.
- benefits
- 1/5
- freshness
- 4/5
- career value
- 4/5
- role clarity
- 5/5
- pay transparency
- 0/5
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 Atomic Machines as an employer.
What you need
- Minimum of 5 years of relevant industry experience or a PhD in a related field
- Practical DFM experience with code that generates geometry under manufacturing constraints
- Working computational geometry ability including 2D boolean operations and polygon offsetting
- Strong software engineering skills in Python and a systems language
- Demonstrated ability to work on novel, poorly specified problems
- Willingness to ground work in physical evidence from the fab
Nice to have
- Exposure to laser micromachining or other subtractive micro-scale processes
- Background in mechanics to reason about part stability during processing
- Experience with combinatorial and geometric optimization
- Machine learning on geometric data
- Experience placing heuristic or learned components in a deterministic pipeline
What you get
- Equity
- Benefits
Worth weighing
- Salary range is $200,000 - $250,000, which may be a consideration for candidates
- The role spans early career through Staff levels, indicating varying expectations based on experience
- The position involves working on complex, novel problems that may require a high degree of creativity and problem-solving
Summarised from Atomic Machines's posting. Read the full original.
Listed by Atomic Machines on their greenhouse job board, last confirmed open on 2026-09-17. PitchMeAI is not the employer.
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