15 of 15 Contract Natural Language Processing Jobs

models. This position is ideal for someone with a strong theoretical linguistics background and experience working with natural language processing (NLP) systems and multilingual data . Key Responsibilities Perform linguistic analyses on large multilingual datasets . Conduct error analysis of AI-generated text , identifying frequent … priorities effectively. Preferred Skills Experience working with low-resource languages . Familiarity with international language classification standards. Experience collaborating with machine learning engineers, NLP researchers, or data scientists . Background in corpus linguistics or linguistic fieldwork . Experience contributing to academic or technical research publications. Basic project management knowledge. ...

empowered the intelligent upgrading and process optimization of relevant business scenarios. Job Requirements: Master's degree or above in Computer Vision, Multimodal Large Modeling, Natural Language Processing, or related fields, with over 8 years of experience in AI-related work. Experience in successfully optimizing model training algorithms … inference acceleration methods such as DeepSpeed, flash-attn, and VLLM. Familiar with multimodal domain algorithms, including basic VLM models such as Llava and QwenVL, NLP domain algorithms such as basic LLM models such as BERT, GPT, and Llama, and CV domain algorithms such as basic CV models such ...

development of innovative solutions. Your Profile Essential skills/knowledge/experience: Proficiency in Python and extensive experience with AI/ML/NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK). Experience with state-of-the-art LLMs (e.g., GPT series, Llama series, Mistral, Claude), including prompt engineering, fine ...

secure, high-integrity systems and services across critical defence, government, and public sector programmes. Key Responsibilities: Design, build, and optimise machine learning models, including NLP, computer vision, and predictive analytics Own the ML lifecycle from data preparation through to training, evaluation, and deployment Implement and maintain MLOps workflows for continuous … data technologies (Spark, Hadoop) and Apache tools Familiarity with Agile and DevOps practices Industry certifications (e.g., TensorFlow Developer, AWS Machine Learning Specialty) Knowledge of NLP, computer vision, and deep learning architectures STEM degree or equivalent experience in AI, Data Science, or related fields If you are ready to take ownership ...

science fundamentals and time-series forecasting. Machine Learning: Strong grasp of ML and deep learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, BERT, LSTM, NLP, Transfer Learning). Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community we have built ...

e.g., Jira) Hands-on experience with a range of databases and storage technologies: Elastic, Mongo, Cassandra, Redis, S3 Desirable Skills PyTorch, AI/ML, NLP, LLMs Experience with the Atlassian Suite, GitHub, Linux CLI Broader data handling and advanced model-driven development exposure To learn more, please do reach ...

e.g., Jira) Hands-on experience with a range of databases and storage technologies: Elastic, Mongo, Cassandra, Redis, S3 Desirable Skills PyTorch, AI/ML, NLP, LLMs Experience with the Atlassian Suite, GitHub, Linux CLI Broader data handling and advanced model-driven development exposure To learn more, please do reach ...

platforms, ML pipelines, and AI products Ensure solutions are scalable, reusable, secure, and cost effective Select appropriate ML/AI techniques (e.g., regression, classification, NLP, forecasting, clustering) 2. Data & Analytics Engineering Alignment Work closely with data engineers to define: Data models and schemas Data quality rules ETL/ELT pipelines … Establish best practices and reusable design patterns Your Profile Essential Skills/Knowledge/Experience Data Science & ML Supervised and unsupervised learning Time series, NLP, recommendation systems (as applicable) Programming Python (NumPy, Pandas, Scikit learn) Optional: R, SQL Data Platforms Relational & NoSQL databases Big data frameworks (Spark, Hive, Databricks) MLOps ...

will be required to go through MOD SC clearance. You will be involved in: Design, build, and optimise machine learning models, including NLP, computer vision, and predictive analytics Own the ML lifecycle from data preparation through training, evaluation, and deployment Implement and maintain MLOps workflows for continuous integration and delivery ...

modern automation tooling. Exposure to testing data-driven applications and distributed systems. Desirable: Experience testing GenAI or LLM-based services. Background in supporting ML, NLP, or data-heavy engineering environments. Familiarity with validating prompt flows, LLM responses, or AI pipelines. Tech Environment: Python, JavaScript, Node.js Performance automation tools API testing ...

Skills & Experience Proven experience delivering AI, automation, or digital transformation programmes Strong understanding of AI/ML and intelligent automation technologies (e.g. RPA, NLP) Excellent stakeholder management and communication skills Experience working in Agile delivery environments Ability to bridge the gap between technical teams and business leaders Clearance Active ...

Responsibilities: Design and implement generative models using state-of-the-art architectures (e.g., GPT, DALL E, Stable Diffusion). Fine-tune and optimize large language models (LLMs) for specific tasks and domains. Build pipelines for data preprocessing, model training, evaluation, and deployment. Collaborate with product, design, and engineering teams … Abilities: Strong programming skills in Python and experience with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers). Solid understanding of deep learning, NLP, and generative modeling techniques . Experience with training and fine-tuning large-scale models . Familiarity with cloud platforms (AWS, GCP, Azure) and MLOps tools. ...

well-defined modelling tasks. Build end to end ML pipelinesfrom feature engineering and preprocessing to deployment ready model outputs. Apply advanced techniques such as NLP, time series forecasting, anomaly detection, optimisation, or LLM/GenAI methods where relevant. Implement model evaluation frameworks using offline metrics, cross validation, online experiments … connectivity and Data Integrations Experience working with large, complex datasets, including data cleaning, feature engineering, and exploratory data analysis. Familiarity with LLMs, NLP techniques, and GenAI frameworks, including embeddings, prompt engineering, or fine tuning. Experience building end to end ML pipelines, including model validation, optimisation, deployment, and monitoring. Understanding ...

post-go-live support. There is also an opportunity to contribute to the integration of broader intelligent automation technologies, including Machine Learning, OCR and NLP, within an established governance framework. Key responsibilities Design, develop and deliver end-to-end automation solutions Review Process Definition Documents (PDDs) and produce Solution Design … Documents (SDDs) Develop Power Automate cloud workflows, RPA workflows and hybrid automation solutions Integrate intelligent automation capabilities such as ML, OCR and NLP where appropriate Support SIT and UAT, including preparation of test plans and test data Work closely with technical and change teams to ensure access, requirements and dependencies ...

development of automation processes. You will work with cutting-edge technology, integrating intelligent automation capabilities (such as Machine Learning, OCR, and NLP) into scalable workflows. Key Responsibilities Development: Design, develop, and implement enterprise-grade automations using Power Automate (cloud flows, desktop flows/RPA, and combined workflows). Solution Design … User Acceptance Testing (UAT), ensuring automations are robust, fit-for-purpose, and align with governance frameworks. Integration: Integrate intelligent automation capabilities (AI, OCR, NLP) into automated processes to enhance functionality. Handover: Manage the smooth transition of automations to the support team during Post Go-Live Support (PGLS), ensuring comprehensive knowledge ...