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NLP/Linguistics Software Engineer

Hatchit
Somerville, USA
Full-time
Junior · 2–4 years experience
Hybrid
Discovered 1 months ago
elasticsearchjavakubernetespython

Full Job Posting

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.

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