126 to 150 of 218 Remote Natural Language Processing Jobs

Software Engineering, or a related field . You have 6+ years of experience in software engineering with at least 3+ years of experience in ML/AI engineering or NLP-related software development. You are an engineer at heart, you enjoy building working systems more than writing research papers. You have strong Python skills and experience in building and maintaining More ❯

and agentic models into real-world forecasting and product platforms. What youll do: Lead a high-performing team of data scientists and engineers Drive AI innovation using LLMs, CV, NLP & generative models Oversee architecture of scalable, cloud-native data platforms Partner with product, tech, and commercial leaders to deliver impact Ensure strong data governance, performance, and ethical AI practices What More ❯

data, or automation-driven projects within financial services or another highly regulated environment. Strong understanding of technology-enabled change, particularly involving data platforms, analytics, or automation tools (e.g. ML, NLP, RPA, GenAI). Excellent stakeholder management and communication skills, with the ability to influence at senior and executive levels. Strong project planning, governance, and risk management skills across both Agile More ❯

data, or automation-driven projects within financial services or another highly regulated environment. Strong understanding of technology-enabled change, particularly involving data platforms, analytics, or automation tools (e.g. ML, NLP, RPA, GenAI). Excellent stakeholder management and communication skills, with the ability to influence at senior and executive levels. Strong project planning, governance, and risk management skills across both Agile More ❯

data, or automation-driven projects within financial services or another highly regulated environment. Strong understanding of technology-enabled change, particularly involving data platforms, analytics, or automation tools (e.g. ML, NLP, RPA, GenAI). Excellent stakeholder management and communication skills, with the ability to influence at senior and executive levels. Strong project planning, governance, and risk management skills across both Agile More ❯

trust team solving big, bold problems. What You’ll Get to Work On Designing and building multi-agent AI architectures using frameworks like LangGraph (or similar) Integrating LLMs and NLP models into workflows for reasoning, automation, and search Leading ML pipeline development , from ingestion to real-time inference Deploying to cloud and edge environments using Terraform, Helm, and Kubernetes (EKS More ❯

trust team solving big, bold problems. What You’ll Get to Work On Designing and building multi-agent AI architectures using frameworks like LangGraph (or similar) Integrating LLMs and NLP models into workflows for reasoning, automation, and search Leading ML pipeline development , from ingestion to real-time inference Deploying to cloud and edge environments using Terraform, Helm, and Kubernetes (EKS More ❯

or related field (e.g. MSc) Scientific thinking skills Track record shipping ML products PhD or other experience in a research environment Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering Strong stats or math background We are a well treated bunch, with awesome benefits! If there's something important to you that's More ❯

recruit a senior researcher to join our rapidly expanding Data and Decision Support Capability. You should have a solid background in Machine Learning (ML) and/or statistical signal processing combined with excellent programming skills in Python and extensive experience in the use of libraries and toolboxes to support efficient development. The right candidate will join our Advanced Information … Processing (AIP) group, specialising in developing novel inference algorithms and the application of AI/ML to sequential (time-series) data and decision making. The candidate will have the opportunity to deliver a wide range of AI/ML research topics for customers across the space, defence, security and commercial sectors as well as into our internal BAE Systems … processing, data fusion, reinforcement learning, agent-based ML, autonomy, ML for signal processing, edge ML, image analysis and computer vision, generative AI, deep fake, LLMs, knowledge graphs, NLP, graph ML and others. You will have the opportunity to work with these colleagues in multi-disciplinary teams. Typical Responsibilities: Lead technical delivery of projects, leading junior researchers. Prepare and More ❯

in agile teams. Key Responsibilities: Lead the architecture and development of AI/ML solutions, ensuring scalable and efficient design. Design and implement ML models and algorithms (classification, regression, NLP, etc.) using modern frameworks. Collaborate with data scientists, engineers, and product teams to transform prototypes into production-grade applications. Optimize model performance and manage end-to-end ML lifecycle (data … experience, with at least 3 years in AI/ML. Strong proficiency in Python , including libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch . Solid understanding of ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP . Hands-on experience with MLOps tools (MLflow, SageMaker, Kubeflow, etc.) and … architecture, and CI/CD pipelines. Proven experience in leading teams, managing stakeholders, and delivering end-to-end AI/ML projects. Nice to Have: Exposure to LLMs (Large Language Models), generative AI , or transformer architectures . Experience with data engineering tools (Spark, Airflow, Snowflake). Prior experience in fintech, healthtech, or similar domains is a plus. More ❯

work alongside MLOps to help build the ML infrastructure for these models to be deployed, and then maintain & scale these efficiently. Experienced ML Engineer, working across LLM, Computer Vision, NLP, Deep Learning Experience with deploying ML models into production Degree in Computer Science, AI, Big Data, or equivalent More ❯

across internal stakeholders to ensure the models being built are improving customer experience, and business efficiency. What we're looking for: Experienced ML Engineer, working across LLM, Computer Vision, NLP, Deep Learning Experience with deploying ML models into production An understanding of emerging technologies - such as Retrieval-Augmented Generation (RAG) and Knowledge Graphs A proactive mindset to identify problems and More ❯

across internal stakeholders to ensure the models being built are improving customer experience, and business efficiency. What we're looking for: Experienced ML Engineer, working across LLM, Computer Vision, NLP, Deep Learning Experience with deploying ML models into production An understanding of emerging technologies - such as Retrieval-Augmented Generation (RAG) and Knowledge Graphs A proactive mindset to identify problems and More ❯

across internal stakeholders to ensure the models being built are improving customer experience, and business efficiency. What we're looking for: Experienced ML Engineer, working across LLM, Computer Vision, NLP, Deep Learning Experience with deploying ML models into production An understanding of emerging technologies - such as Retrieval-Augmented Generation (RAG) and Knowledge Graphs A proactive mindset to identify problems and More ❯

across internal stakeholders to ensure the models being built are improving customer experience, and business efficiency. What we're looking for: Experienced ML Engineer, working across LLM, Computer Vision, NLP, Deep Learning Experience with deploying ML models into production An understanding of emerging technologies - such as Retrieval-Augmented Generation (RAG) and Knowledge Graphs A proactive mindset to identify problems and More ❯

across internal stakeholders to ensure the models being built are improving customer experience, and business efficiency. What we're looking for: Experienced ML Engineer, working across LLM, Computer Vision, NLP, Deep Learning Experience with deploying ML models into production An understanding of emerging technologies - such as Retrieval-Augmented Generation (RAG) and Knowledge Graphs A proactive mindset to identify problems and More ❯

in biological sciences or pharmaceutical industry Preferred Skills Experience with Docker and multi-container architectures Exposure to scientific datasets (e.g. genomics, proteomics) Familiarity with AI/ML deployment, especially NLP tools (LangGraph, AutoGen) Understanding of AI/ML evaluation and iterative improvement Some experience with frontend development (e.g. React) If this opportunity aligns with your experience and interests, please apply More ❯

in biological sciences or pharmaceutical industry Preferred Skills Experience with Docker and multi-container architectures Exposure to scientific datasets (e.g. genomics, proteomics) Familiarity with AI/ML deployment, especially NLP tools (LangGraph, AutoGen) Understanding of AI/ML evaluation and iterative improvement Some experience with frontend development (e.g. React) If this opportunity aligns with your experience and interests, please apply More ❯

to non-technical stakeholders. Facilitate workshops and knowledge-sharing sessions with programme teams. Required Skills & Experience Strong understanding of AI/ML concepts, frameworks, and deployment models. Familiarity with NLP, predictive analytics, and generative AI capabilities. Proven experience in consulting or advisory roles within AI or technology strategy. Ability to present complex technical ideas in business-friendly language. Experience defining More ❯

Skillsets: Applied AI Knowledge: Practical experience integrating and consuming AI/ML models within a production environment. Familiarity with common AI/ML concepts (e.g., supervised/unsupervised learning, NLP, computer vision fundamentals). Experience working with AI APIs (e.g., OpenAI, Google Cloud AI, AWS AI Services) or integrating with custom-built models. Understanding of data processing for AI … both technical and non-technical stakeholders. Bonus Points For: Experience in the iGaming, sports, or entertainment industry. Familiarity with Web3 technologies, NFTs, or blockchain. Experience with real-time data processing (e.g., WebSockets, Kafka). Contributions to open-source projects or a strong GitHub profile. Experience with A/B testing frameworks and analytics platforms. WHAT WE OFFER Fully remote More ❯

work collaboratively in a team environment Nice to Have (But Not Required): Experience from a university project, hackathon, or internship involving AI or machine learning Understanding of neural networks, NLP, or computer vision concepts Experience using Jupyter notebooks, Git, or cloud platforms (AWS, GCP, Azure) Knowledge of SQL or data wrangling techniques What You’ll Gain Real-World Experience : Work … techniques, and best practices Certification Support : Assistance in pursuing relevant AI/ML certifications (e.g. Google AI, AWS ML, TensorFlow Developer) Career Growth : Opportunities to specialise in areas like NLP, computer vision, or AI engineering Community & Culture : Be part of a collaborative, diverse, and forward-thinking tech team Excellent Company Benefits 25+ Days Annual Leave , plus bank holidays Hybrid Working More ❯

work collaboratively in a team environment Nice to Have (But Not Required): Experience from a university project, hackathon, or internship involving AI or machine learning Understanding of neural networks, NLP, or computer vision concepts Experience using Jupyter notebooks, Git, or cloud platforms (AWS, GCP, Azure) Knowledge of SQL or data wrangling techniques What You’ll Gain Real-World Experience : Work … techniques, and best practices Certification Support : Assistance in pursuing relevant AI/ML certifications (e.g. Google AI, AWS ML, TensorFlow Developer) Career Growth : Opportunities to specialise in areas like NLP, computer vision, or AI engineering Community & Culture : Be part of a collaborative, diverse, and forward-thinking tech team Excellent Company Benefits 25+ Days Annual Leave , plus bank holidays Hybrid Working More ❯

work collaboratively in a team environment Nice to Have (But Not Required): Experience from a university project, hackathon, or internship involving AI or machine learning Understanding of neural networks, NLP, or computer vision concepts Experience using Jupyter notebooks, Git, or cloud platforms (AWS, GCP, Azure) Knowledge of SQL or data wrangling techniques What You’ll Gain Real-World Experience : Work … techniques, and best practices Certification Support : Assistance in pursuing relevant AI/ML certifications (e.g. Google AI, AWS ML, TensorFlow Developer) Career Growth : Opportunities to specialise in areas like NLP, computer vision, or AI engineering Community & Culture : Be part of a collaborative, diverse, and forward-thinking tech team Excellent Company Benefits 25+ Days Annual Leave , plus bank holidays Hybrid Working More ❯

work collaboratively in a team environment Nice to Have (But Not Required): Experience from a university project, hackathon, or internship involving AI or machine learning Understanding of neural networks, NLP, or computer vision concepts Experience using Jupyter notebooks, Git, or cloud platforms (AWS, GCP, Azure) Knowledge of SQL or data wrangling techniques What You’ll Gain Real-World Experience : Work … techniques, and best practices Certification Support : Assistance in pursuing relevant AI/ML certifications (e.g. Google AI, AWS ML, TensorFlow Developer) Career Growth : Opportunities to specialise in areas like NLP, computer vision, or AI engineering Community & Culture : Be part of a collaborative, diverse, and forward-thinking tech team Excellent Company Benefits 25+ Days Annual Leave , plus bank holidays Hybrid Working More ❯

techniques to communicate analytical findings in a compelling and accessible way. Monitoring and fine-tuning model performance to ensure continuous accuracy and reliability. Using advanced machine learning techniques (including NLP, deep learning, and time-series forecasting) to solve complex business challenges. Contributing to the development of robust MLOps processes for deployment, monitoring, and retraining of models. About You You're … skills in Python, with deep familiarity across ML and data libraries (pandas, numpy, scipy, scikit-learn, tensorflow, pytorch). A broad understanding of machine learning and statistical methods, including NLP, deep learning, Bayesian inference, time-series forecasting, and recommendation systems. Hands-on experience with cloud platforms such as AWS, GCP, or Azure, and exposure to tools like Databricks or Dataiku. More ❯