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Nlp Transformers Jobs (NOW HIRING)

United IT

GenAI NLP ML Engineer

Austin, TX

GenAI NLP ML Engineer Location: Austin TX Key Responsibilities: * 10+ yrs experience minimum ... and Hugging Face Transformers for model development and optimization. * Design, develop, and ...

hireVouch

Senior AI Research Scientist (NLP)

Continuously research and apply the latest techniques in NLP to supply chain problems ... Proficiency in Python and libraries such as pytorch and huggingface transformers. * Experience with ...

Hirevouch

Senior AI Research Scientist (NLP)

Continuously research and apply the latest techniques in NLP to supply chain problems ... Proficiency in Python and libraries such as pytorch and huggingface transformers. * Experience with ...

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How much do nlp transformers jobs pay per year?

As of Jun 9, 2026, the average yearly pay for nlp transformers in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What are NLP Transformers?

NLP Transformers are a type of deep learning model designed to process and understand natural language data. Introduced in the paper 'Attention is All You Need', transformers use attention mechanisms to capture relationships between words in a sentence, regardless of their position. This architecture has become the foundation for many advanced language models, such as BERT and GPT. Transformers have significantly improved performance in tasks like translation, summarization, and question answering within natural language processing.

What are the key skills and qualifications needed to thrive as an NLP Transformers Engineer, and why are they important?

To thrive as an NLP Transformers Engineer, you need a strong background in machine learning, natural language processing, and proficiency in programming languages like Python, often supported by a degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, and libraries like Hugging Face Transformers, as well as knowledge of cloud platforms, is essential. Strong problem-solving skills, collaboration, and effective communication set exceptional candidates apart in this role. These skills and qualities are crucial for developing, optimizing, and deploying cutting-edge NLP solutions that drive business value.

What are the typical collaboration dynamics for NLP Transformers specialists within a development team?

NLP Transformers specialists often work closely with data scientists, machine learning engineers, and software developers to design, implement, and optimize transformer-based models for natural language processing tasks. Collaboration usually involves regular meetings to discuss project goals, data preprocessing strategies, model architecture, and evaluation metrics. Specialists may also coordinate with product managers or domain experts to ensure that models align with user needs and business objectives. Open communication and code reviews are common practices to maintain high-quality solutions and foster continuous learning within the team.

GenAI NLP ML Engineer

United IT

Austin, TX

Other

Posted 2 days ago

Job description

GenAI NLP ML Engineer

Location: Austin TX

Key Responsibilities:
  • 10+ yrs experience minimum
  • Collaborate and manage with data science, engineering, and GenAI teams to deploy and scale machine learning and generative AI models.
  • Operationalize complex ML and GenAI models into production environments, ensuring end-to-end deployment and monitoring.
  • Apply knowledge of standard ML algorithms (Regression, Classification), NLP concepts (sentiment analysis, topic modeling, TF-IDF), and Generative AI techniques (LLMs, prompt engineering, embeddings).
  • Apply knowledge of Retrieval Augmented Generation using embedding models and Vector databases.
  • Manage delivery of GenAI/LLM features (prompt engineering, evaluation metrics, retrieval patterns, guardrails) and productionizing Q&A/assistant workflows.
  • Lead Platform and DevOps: CI/CD, containerization, observability, and environment automation in a major cloud - ideally working experience on Google.
  • Utilize Python and ML/GenAI libraries such as scikit-learn, PySpark, pandas and Hugging Face Transformers for model development and optimization.
  • Design, develop, and maintain adaptable data pipelines tailored to use-case-specific requirements.
  • Integrate ML and GenAI use cases into business workflows, ensuring seamless data exchange with upstream and downstream systems.
  • Build and maintain pipelines for model performance metrics, supporting Model Risk Oversight and compliance review cadences.
  • Develop runbooks and provide ongoing support for operationalized models to ensure reliability and scalability.

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