NLP/Linguistics Software Engineer

Babel Street; Somerville (MA); On-site; USD 100,000 - 140,000; Full time

Job summary

Babel Street in Somerville, MA is seeking an NLP/Linguistics Software Engineer to join their Analytics Group. This execution-focused builder role handles NLP algorithms, search engines, and data science techniques to advance their analytics platform and its record matching functionality.

You will work with senior engineers to translate linguistic theory into production-ready features, optimize Elasticsearch components, and help ship scalable APIs for AI-native systems, with opportunities to grow

Qualifications

• Bachelor's degree in Computer Science, Linguistics, or related technical field.
• 2–4 years of professional software engineering experience.
• Proficiency in Java or Python.
• Strong problem-solving and collaboration skills.

Responsibilities

• Implement and maintain analytics platform components, including record matching.
• Bridge linguistic theory with practical software features.
• Optimize search internals and data modeling with Elasticsearch.
• Collaborate in Agile sprint planning with senior engineers.
• Design scalable APIs and architectures for AI-native platform.

Skills

Problem solving

Education

Bachelor's degree in Computer Science, Linguistics, or related technical field

Tools

Java

Python

Elasticsearch

Job description

hatch I.T. is partnering with Babel Street to find an NLP/Linguistics Software Engineer. Please see details below:

About the Role

Babel Street is looking for a Software Engineer to join their 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 their analytics platform, focusing specifically on their 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.

About the Company

Babel Street is the trusted technology partner for the world’s most advanced identity intelligence and risk operations. They 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 empowers 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.

What you will do:

• 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 will bring:

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:

• 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.

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.