Lila Sciences
Microfabrication Scientist I/II
Cambridge, MA USA · Mid · Full-time
Sponsorship not specified$108k-$170kDetected 37 days ago
PythonMachine LearningSEMRecruitingElectrical EngineeringResearch
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odds of building a lasting career here
57Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds (Level III)83
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~45% per draw at Level III). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
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from this employer's Department of Labor filings
Files H-1B transfers
10 transfer filings in the last year, covering 10 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
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About the role
- Your Impact at LILA As a Microfabrication Scientist on the Vacuum Synthesis team at Lila Sciences, you will serve as the primary contributor to the fabrication of prototype devices used to probe and characterize the of novel materials.
- The experimental outputs will feed directly into closed-loop discovery campaigns.
- Your final offer will reflect your background, expertise, and expected impact.
Responsibilities
- Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.
- Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges.
- Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.
Nice to have
- Execute cleanroom processes, including lithography, wet/dry etching, and thin-film deposition.
- Characterize films and devices using profilometry, ellipsometry, SEM, and electrical probing.
- Integrate fabrication processes into automated and high-throughput workflows.
- Translate experimental goals into manufacturable process steps with materials scientists and engineers.
- Bachelor's degree in Materials Science, Electrical Engineering, Chemical Engineering, Physics, or a closely related field
- advanced degree (M.S. or Ph.D.) preferred.
- 5+ years of hands-on cleanroom experience in research, development, or manufacturing.
- Deep expertise in thin-film deposition, including recipe development and troubleshooting.
Compensation
- We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.
- International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions
- Expected Base Salary Range
- $108,000 - $170,000 USD
- USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.
Benefits
- U.S. Benefits.
- Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage
- employer-paid life and disability insurance
- flexible time off with generous company wide holidays
- paid parental leave
- an educational assistance program
- commuter benefits, including bike share memberships for office based employees
- International Benefits.
- Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region.
Visa & Work Authorization
- al employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status
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This listing is sourced directly from Lila Sciences's careers page and normalized into a canonical job model.