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Language Engineer Jobs (NOW HIRING)

Oxy

Senior AI Language Model Engineer

Houston, TX

$99K - $137K/yr

Design workflows for language model deployment. Perform prompt engineering, pre-processing, and post-processing to optimize output suitability. * Fine-tune and optimize multi-agentic systems to ...

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$39K

$101.8K

$137.5K

How much do language engineer jobs pay per year?

As of Jun 19, 2026, the average yearly pay for language engineer in the United States is $101,752.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $116,500.00 per year, depending on experience, location, and employer.

What are the typical daily responsibilities of a Language Engineer?

Language Engineers typically spend their days developing, testing, and improving language models and algorithms used in applications such as chatbots, voice assistants, and translation tools. They collaborate closely with data scientists, software engineers, and linguists to collect and annotate data, refine language processing workflows, and address real-world linguistic challenges. Regular tasks may include designing rule-based systems, implementing machine learning models, evaluating system performance, and troubleshooting language-specific issues. This role often requires balancing independent work with team collaboration to ensure language technologies meet both technical and user experience goals.

What is a Language Engineer job?

A Language Engineer designs, develops, and optimizes language-related technologies, such as natural language processing (NLP) models, speech recognition systems, and machine translation tools. They work with linguistic data, improve language models, and create rules and algorithms to enhance text and speech processing. This role often involves collaborating with software engineers, data scientists, and linguists to refine language-based AI systems. Language Engineers also help expand language support for AI applications by curating datasets and improving system accuracy.

What are the key skills and qualifications needed to thrive in the Language Engineer position, and why are they important?

To thrive as a Language Engineer, you need a strong background in computational linguistics, natural language processing (NLP), and programming languages such as Python or Java, often supported by a degree in computer science, linguistics, or related fields. Familiarity with NLP libraries (e.g., NLTK, spaCy), machine learning frameworks, and tools for text annotation and data processing is highly beneficial. Strong problem-solving abilities, attention to detail, and effective communication skills are crucial soft skills in this role. These competencies enable Language Engineers to build robust language models, collaborate across interdisciplinary teams, and address complex language-related challenges in technology products.

More about Language Engineer jobs
What cities are hiring for Language Engineer jobs? Cities with the most Language Engineer job openings:
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Language Engineer jobs near you
Infographic showing various Language Engineer job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 94% Full Time, 1% Part Time, and 4% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $101,752 per year, or $48.9 per hour.

Principal Engineer - Code Analysis & Compilers ::Remote / Hybrid

Talent Movers

Mountain View, CA • Remote

Contractor

Posted 20 days ago

Job description

Job Title: Principal Engineer – Code Analysis & Compilers

Location: Remote / Hybrid

Negotiate and Share

FTE Only

 

We are looking for a Language Engineer who understands that reliable code generation requires deep structural understanding, not just large language models. You will be a founding engineer of a high-visibility product team with the autonomy to define technical direction.

The Challenge 

You will build the core engine responsible for ingesting, parsing, and analyzing millions of lines of legacy code (SQL, SAS, etc.). Your work will bridge the gap between Static Analysis and Generative AI, ensuring our models operate with mathematical precision.

What You Will Do

  • Deep Code Parsing: Design and implement robust parsers to convert legacy codebases into structured data representations (using tools like ANTLR or similar libraries).
  • Static Analysis: Build algorithms to trace data lineage, identify dependencies, and extract logic from unstructured code.
  • AI Integration: Collaborate with AI engineers to feed high-fidelity structural context into our generative models.
  • Performance Engineering: Optimize the processing of massive code repositories to run efficiently at scale.

What We Need

  • Core CS Fundamentals: Deep understanding of Data Structures, Algorithms, and Graph Theory.
  • Language Theory: Experience with Abstract Syntax Trees (ASTs), Lexers, and Parsers is non-negotiable. You understand why Regex is insufficient for code analysis.
  • Engineering Excellence: Strong proficiency in Python and experience building scalable backend systems.
  • Problem Solving: You love reverse-engineering how languages work and finding patterns in chaos.

Preferred Experience

  • Experience with ANTLR, Tree-sitter, or SQLGlot.
  • Background in building transpilers, linters, or code migration tools.
  • Familiarity with Vector Databases or LLM orchestration frameworks (LangChain/LlamaIndex) is a plus.