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NLP/Linguistics Software Engineer

Babel Street · Somerville, Massachusetts, United States · Hybrid · Active · Greenhouse

Job facts

FieldValue
CompanyBabel Street
TitleNLP/Linguistics Software Engineer
Normalized title-
Department / teamInnovation
LocationSomerville, MA, United States
Work modelHybrid / Hybrid
Employment type-
Salary-
Statusactive
ATS providerGreenhouse
Posted / first seen2026-06-16 / 2026-06-17
Changed / last seen2026-06-17 / 2026-06-21

Related slices

PageWhat it containsOpen
Company jobsActive postings from Babel Street.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Greenhouse.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in Somerville.Open
Department jobsActive postings in Innovation.Open
Work model jobsActive Hybrid postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyBabel Street
Sourcefa01bb13-04cb-4c5a-86aa-67331c389dbd
ATS providerGreenhouse

Description

Babel Street is the trusted technology partner for the world’s most advanced identity intelligence and risk operations. We deliver advanced AI and data analytics solutions providing unmatched, analysis-ready data regardless of language, proactive risk identification, 360-degree insights, high-speed automation, and seamless integration into existing systems. Babel Street empower s government and commercial organizations to transform high-stakes identity and risk operations into a strategic advantage . The actionable insights we deliver safeguard lives and protect critical assets around the world . Babel Street is headquartered in Reston, Virginia , with regional offices in Boston, MA and Cleveland, OH, and international offices in Australia, Canada, Israel, Japan, and the U.K. For more information, visit www. babelstreet.com . ROLE SUMMARY Babel Street is looking for a Software Engineer to join our Analytics Group. This is an execution-focused "builder" role for an engineer early in their career who wants to work at the intersection of NLP algorithms, search engines, and data science techniques. In this role, you will help create the next generation of architecture and components for our analytics platform, focusing specifically on our record matching functionality. You will bridge the gap between linguistic theory and practical AI applications, helping us implement practical, innovative text analytics and AI-driven features. You will work closely with senior engineers to learn how to deliver software that is safe, reliable, and production-ready. WHY THIS ROLE MATTERS The record matching functionality is where Babel Street’s signals become usable intelligence. Do you care about provenance, explainability, and trust? When a match decision affects whether someone is onboarded or investigated, "the model said so" is not good enough. You will help build systems where every match is defensible, auditable, and tunable — a rare luxury in modern ML-heavy stacks. Do you speak multiple languages? Since our platform processes data from around the globe, your linguistic insights can directly inform how we build and polish the NLP and computational linguistics components that make our record matching world-class. WHAT YOU’LL DO (KEY RESPONSIBILITIES) Implement and Maintain: Write high-quality, maintainable code to support the analytics platform and its record matching components. Bridge Theory and Practice: Take theoretical ideas from linguistics and data science and implement them as practical software features. Support Search Internals: Help optimize and maintain search engine components, including Elasticsearch data modeling and performance tuning. Collaborate and Learn: Participate in agile sprint planning and work daily with senior partners to translate project requirements into technical solutions. Build Scalable Systems: Assist in designing and shipping robust APIs and scalable architectures that integrate into our AI-native platform. WHAT YOU BRING (QUALIFICATIONS) Required: 2–4 years of professional software engineering experience (including high-impact internships or projects). Proficiency in Java (our core analytics language) or Python (for AI/ML integrations). Problem Solver: Ability to work across teams and make steady progress in ambiguous problem spaces. Educational Foundation: Bachelor's degree in Computer Science, Linguistics, or a related technical field. Preferred (Nice to Have) Foundation in Data Science: Experience with data quality evaluation, data annotation, or guideline design, preferably for linguistics. Familiarity with Elasticsearch internals or other search/retrieval-based systems. Exposure to computational linguistics or natural language processing (NLP). Interest in Kubernetes and cloud-native architectures. WHAT SUCCESS LOOKS LIKE (FIRST SIX MONTHS) Month 1–2: Ramp up on the analytics stack and record matching architecture; ship your first initial changes to production. Month 3–4: Take ownership of a specific component or pipeline improvement with guidance, including full testing and documentation. Month 5–6: Deliver a measurable improvement to record matching quality or pipeline reliability and contribute to team design discussions. Benefits at Babel Street (just to name a few...) Health Benefits: Babel Street covers 85-100% monthly premium costs for Medical, Dental, Vision, Life & Disability insurances – for you and your family! Retirement Plans: Babel Street offers both a Traditional and Roth 401(K) with a very competitive match. Unlimited Flexible Leave: We trust our employees to manage their own time and balance their personal and work lives. Holidays: Babel Street provides employees with 12 paid Federal Holidays Tuition Reimbursement: We are committed to investing in our employees. One way we do that is with our Tuition Reimbursement Program for continuing education. Babel Street is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. Further, Babel Street will not discriminate against applicants for inquiring about, discussing or disclosing their pay or, in certain circumstances, the pay of their co‐worker, Pay Transparency Nondiscrimination . In addition, Babel Street's policy is to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations and ordinances where a particular employee works. Upon request, we will provide you with more information about such accommodations. Range for this position based on qualifications and experience $100,000 — $120,000 USD

Full job record

Job IDc1ac0165ab764da4ec40a80886315b5ac8b5d5a1
Org ID8851339b-9cac-4e2b-b537-ec4382bdf1bf
Source IDfa01bb13-04cb-4c5a-86aa-67331c389dbd
Board IDfa01bb13-04cb-4c5a-86aa-67331c389dbd
Providergreenhouse
Provider Job Key8008713
TitleNLP/Linguistics Software Engineer
Normalized Title
Statusactive
Activeyes
Location TextSomerville, Massachusetts, United States
DepartmentInnovation
Team
Employment Type
Workplace Typehybrid
Remote Policyhybrid
CountryUnited States
RegionMA
CitySomerville
Salary Raw
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://job-boards.greenhouse.io/babelstreet/jobs/8008713
Apply URLhttps://job-boards.greenhouse.io/babelstreet/jobs/8008713
First Seen At2026-06-17 07:39:39Z
Last Seen At2026-06-21 07:38:39Z
Last Checked At2026-06-21 07:38:39Z
Last Changed At2026-06-17 07:39:39Z
Inactive At
Source Posted At2026-06-16 19:38:14Z
Source Updated At2026-06-16 19:38:14Z
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=greenhouse/board=babelstreet/date=2026-06-21/2026-06-21T07-38-39-380Z-933f7971b0b6e3cfe268cc617cbec98fb5b77170b24abd56a2e36883a0bce421.json
Event Fields
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Parsed Structured
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Extensions
{}
Native Structured
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