<p>We are seeking an experienced NLP Engineer to join a forward-looking data science team. The successful candidate will design, implement and productionise natural language processing systems that deliver measurable business value. This role suits someone who enjoys solving language problems, mentoring peers and collaborating across product and engineering teams.</p>
<p>This job description outlines the responsibilities, required skills and qualifications for an NLP Engineer. It is intended for HR professionals, recruiters and staffing agencies who wish to attract top talent in natural language processing and machine learning.</p>
<h2>NLP Engineer Job Profile</h2>
<p>The NLP Engineer designs and implements algorithms and models to process and understand human language. They translate business requirements into robust architectures and scalable solutions that integrate with existing data platforms.</p>
<p>Working closely with data scientists and software engineers, the role focuses on model development, evaluation and deployment, plus improving data pipelines and inference performance in production environments.</p>
<h2>NLP Engineer Job Description</h2>
<p>An NLP Engineer is responsible for end-to-end development of language solutions, including data ingestion, annotation, model training, evaluation and deployment. They select appropriate architectures such as transformer-based models, fine-tune pre-trained networks and build feature pipelines to support tasks like classification, entity recognition, question answering and summarisation.</p>
<p>The role requires pragmatic engineering to ensure models are efficient, explainable and reliable. Candidates will implement validation protocols, monitor drift and maintain continuous integration and delivery for ML components. Collaboration with product owners will refine use cases, define success metrics and plan A/B tests to measure impact.</p>
<p>In addition to model work, the NLP Engineer will optimise pre-processing steps such as tokenisation, normalisation and subword handling, and will integrate libraries and frameworks like spaCy, NLTK, TensorFlow or PyTorch. Familiarity with cloud platforms and container technologies is expected to manage scalable inference and batch processing jobs.</p>
<h2>NLP Engineer Duties and Responsibilities</h2>
<ul>
<li>Design, develop and productionise NLP models and services for real-world applications.</li>
<li>Pre-process large textual datasets and manage annotation workflows.</li>
<li>Fine-tune transformer models and build custom architectures as required.</li>
<li>Optimise model inference for latency and throughput in production.</li>
<li>Implement evaluation metrics and create reproducible validation pipelines.</li>
<li>Collaborate with data scientists, software engineers and product managers to define requirements.</li>
<li>Establish monitoring, logging and alerting for deployed models to detect drift or performance degradation.</li>
<li>Document models, experiments and deployment procedures to meet governance standards.</li>
<li>Mentor junior engineers and contribute to team best practices for ML engineering and data handling.</li>
<li>Stay current with research and propose suitable techniques to improve accuracy and efficiency.</li>
</ul>
<h2>NLP Engineer Requirements and Qualifications</h2>
<ul>
<li>Degree in Computer Science, Computational Linguistics, Mathematics or a related discipline.</li>
<li>Proven experience in NLP model development and deployment in a commercial setting.</li>
<li>Strong programming skills in Python and familiarity with ML libraries such as PyTorch or TensorFlow.</li>
<li>Experience with transformer models, BERT, GPT or similar architectures and transfer learning.</li>
<li>Knowledge of NLP toolkits, including spaCy, NLTK or Hugging Face Transformers.</li>
<li>Practical experience with data engineering, SQL and handling large text corpora.</li>
<li>Understanding of MLOps practices, CI/CD pipelines, Docker and Kubernetes for model serving.</li>
<li>Ability to evaluate models using appropriate metrics and design reliable test strategies.</li>
<li>Excellent analytical, problem-solving and communication skills with a collaborative attitude.</li>
<li>Experience with cloud platforms such as AWS, GCP or Azure is desirable.</li>
</ul>