{"id":924420,"url":"https://alion.io/job/lila-sciences-scientist-iii-characterization-and-composition-analysis","title":"Scientist I/II, Characterization and Composition Analysis","company":{"id":65163,"name":"Lila Sciences","domain":"lila.ai","url":"https://alion.io/company/lila-ai","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":87,"open_postings":56,"ghost_share":0,"stale_share":0.304,"repost_share":0,"time_to_fill_p50_days":70,"computed_at":"2026-10-01T05:45:00Z"}},"role":"Science & Research","role_family":"Science & Research","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Cambridge, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":108000,"max":170000,"currency":"USD","period":"year","gross":null,"usd_annual":170000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Ray","optional":false}],"status":"live","first_seen_at":"2026-09-15T00:39:38Z","employer_posted_date":"2026-09-15","last_verified_at":"2026-10-02T01:52:16Z","board_verified":true,"closed_at":null,"days_open":17,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":17},"description":"Your Impact at LILA\nLila Sciences is seeking a Scientist I/II, Characterization and Composition Analysis to join the Materials Science team within the Autonomous Science Platform. The Autonomous Science Platform combines experimental science, automation, AI, and software to accelerate materials discovery. This role turns elemental measurements into trusted, machine-readable composition data that supports scientific decisions, automated workflows, and model development.\nThis is a hybrid experimental and software-facing role, centered on hands-on characterization with substantial analyzer development. You will work with X-ray fluorescence (XRF), SEM-based energy-dispersive spectroscopy (SEM-EDS), wavelength-dispersive spectroscopy (WDS), and related analytical instruments. You will develop and validate methods, prepare standards and calibrations, execute measurements, interpret spectra, and troubleshoot issues from instrument, sample-preparation, and data-quality.\nYou will also design, write, and maintain the analyzer software behind these workflows. Partnering with AI, software, and automation teams, you will build spectral processing, quantification, automated data ingestion, metadata, provenance, and quality-control systems that make characterization outputs reliable, traceable, and useful at scale.\nThe ideal candidate is credible at both the instrument and the keyboard: strong experimental judgment in elemental characterization, paired with the ability to turn measurement expertise into shared, tested code and production-quality data workflows.\nWhat You'll Be Building\nOwn data quality and integrity for elemental and materials characterization workflows.\nDevelop XRF, EDS, and WDS methods, calibrations, and QC procedures.\nPrepare standards, run samples, interpret spectra, and troubleshoot measurement issues.\nLead investigations for anomalous or out-of-specification data and determine data validity.\nDesign, write, and maintain analyzer software for spectral processing and quantification in partnership with machine learning team.\nBuild automated data ingestion, metadata, provenance, and quality-control workflows.\nMaintain instrument readiness through calibration, documentation, SOPs, and troubleshooting.\nSupport safe operation of general materials characterization workflows (profilometry, XRD, SEM).\nHelp evaluate, bring online, and develop methods for new analytical detectors as we expand characterization capability.\nCollaborate with hardware, automation, AI, and software teams to scale trusted data generation.\nWhat You'll Need to Succeed\nPhD in Materials Science, Chemistry, Physics, Engineering, or a related field, or M.S. with equivalent hands-on characterization experience.\nHands-on experience with XRF, SEM-EDS, and WDS for elemental analysis.\nIn-depth knowledge of the physical principles behind XRF, EDS, and WDS analysis, including signal generation, matrix effects, calibration, quantification, and common sources of error.\nStrong understanding of calibration, quantification, spectral interpretation, and data-quality control.\nExperience preparing standards, validating methods, and troubleshooting measurement issues.\nExperience writing analysis notebook and maintaining shared, tested code in a version-controlled codebase.\nProficiency with Python or an equivalent coding environment for data analysis, automation, or analyzer development.\nAbility to translate characterization workflows into reliable, structured, machine-readable data.\nClear communication skills for working across scientific, AI, automation, and software teams.\nBonus Points For\nExperience with EPMA or related elemental microanalysis workflows.\nExperience with broader characterization techniques such as electron microscopy, optical microscopy, XRD, XPS, ICP-OES, ICP-MS, SIMS, or related analytical methods.\nFamiliarity with spectral quantification or analysis tools such as fundamental parameter models, PyMCA, DTSA-II, Probe Software, BadgerFilm, or similar packages.\nExperience developing calibration workflows, reference standards, SOPs, or QC systems for analytical instruments.\nExperience building training datasets or automated analysis pipelines from instrument data.\nCompensation\nWe offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\nU.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; and a company subsidized lunch program.\nInternational 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; international salaries are set to local market.\nExpected Base Salary Range\n$108,000—$170,000 USD\nAbout LILA\nLila 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.\nLILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.\nGuided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.\nWe’re All In\nLila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.\nInformation you provide during your application process will be handled in accordance with our Candidate Privacy Policy.\nA Note to Agencies\nLila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.","description_format":"text","description_chars":6833,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity","Flexible time off","Parental leave"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Materials Science & Nanotechnology","Laboratory & Pharmaceutical Robotics","AI Research Labs","AI for Science"],"lifecycle":[{"event":"open","at":"2026-09-15T05:18:50Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":16,"expected_fill_days":70,"reasons":["conf:4","velocity","win:early","comp:brand"],"computed_at":"2026-10-01T05:45:00Z"},"pay":{"stated_usd_annual":170000,"is_top_pay":true},"html_url":"https://alion.io/job/lila-sciences-scientist-iii-characterization-and-composition-analysis","json_url":"https://alion.io/job/lila-sciences-scientist-iii-characterization-and-composition-analysis.json","meta":{"generated_at":"2026-10-02T03:09:50Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":4356,"day_limit":5000,"remaining_today":644,"minute_limit":60,"resets_at":"2026-10-03T00:00:00Z"}}}