26 to 50 of 9,166 Permanent Artificial Intelligence Jobs

You will work alongside data scientists, ML engineers, and business stakeholders to understand requirements, design and build robust data pipelines, and deliver end-to-end analytics and ML/AI capabilities. Key Responsibilities Design, build, and maintain scalable data pipelines and Delta Lake architectures in Databricks on AWS. Develop and enhance the Front Office data warehouse to ensure performance, reliability … and data quality for trading analytics. Partner with data scientists and quants to prepare ML-ready datasets and support the development of production-grade ML/AI pipelines. Implement and maintain CI/CD pipelines, testing frameworks, and observability tools for data engineering workflows. Contribute to MLOps practices, including model tracking, deployment, and monitoring using MLflow and Databricks tools. Participate More ❯

You will work alongside data scientists, ML engineers, and business stakeholders to understand requirements, design and build robust data pipelines, and deliver end-to-end analytics and ML/AI capabilities. Key Responsibilities Design, build, and maintain scalable data pipelines and Delta Lake architectures in Databricks on AWS. Develop and enhance the Front Office data warehouse to ensure performance, reliability … and data quality for trading analytics. Partner with data scientists and quants to prepare ML-ready datasets and support the development of production-grade ML/AI pipelines. Implement and maintain CI/CD pipelines, testing frameworks, and observability tools for data engineering workflows. Contribute to MLOps practices, including model tracking, deployment, and monitoring using MLflow and Databricks tools. Participate More ❯

You will work alongside data scientists, ML engineers, and business stakeholders to understand requirements, design and build robust data pipelines, and deliver end-to-end analytics and ML/AI capabilities. Key Responsibilities Design, build, and maintain scalable data pipelines and Delta Lake architectures in Databricks on AWS. Develop and enhance the Front Office data warehouse to ensure performance, reliability … and data quality for trading analytics. Partner with data scientists and quants to prepare ML-ready datasets and support the development of production-grade ML/AI pipelines. Implement and maintain CI/CD pipelines, testing frameworks, and observability tools for data engineering workflows. Contribute to MLOps practices, including model tracking, deployment, and monitoring using MLflow and Databricks tools. Participate More ❯

You will work alongside data scientists, ML engineers, and business stakeholders to understand requirements, design and build robust data pipelines, and deliver end-to-end analytics and ML/AI capabilities. Key Responsibilities Design, build, and maintain scalable data pipelines and Delta Lake architectures in Databricks on AWS. Develop and enhance the Front Office data warehouse to ensure performance, reliability … and data quality for trading analytics. Partner with data scientists and quants to prepare ML-ready datasets and support the development of production-grade ML/AI pipelines. Implement and maintain CI/CD pipelines, testing frameworks, and observability tools for data engineering workflows. Contribute to MLOps practices, including model tracking, deployment, and monitoring using MLflow and Databricks tools. Participate More ❯

You will work alongside data scientists, ML engineers, and business stakeholders to understand requirements, design and build robust data pipelines, and deliver end-to-end analytics and ML/AI capabilities. Key Responsibilities Design, build, and maintain scalable data pipelines and Delta Lake architectures in Databricks on AWS. Develop and enhance the Front Office data warehouse to ensure performance, reliability … and data quality for trading analytics. Partner with data scientists and quants to prepare ML-ready datasets and support the development of production-grade ML/AI pipelines. Implement and maintain CI/CD pipelines, testing frameworks, and observability tools for data engineering workflows. Contribute to MLOps practices, including model tracking, deployment, and monitoring using MLflow and Databricks tools. Participate More ❯

Working arrangement: United Kingdom (Remote - work from anywhere in the UK) Build AI Systems That Make Finance Simpler, Smarter, and More Inclusive At BJAK, we're using AI to make insurance and financial services easier to access, understand, and afford for millions across Southeast Asia. As a AI/ML Software Engineer, you'll help build the intelligent systems that … ideas shape real-world outcomes every day. Why This Role Matters Your work will directly impact user experience, efficiency, and platform intelligence You'll contribute to production-grade AI systems that serve millions You'll collaborate across functions and build scalable ML tools from the ground up You'll grow quickly in a lean, high-impact engineering environment What … data preprocessing, feature engineering, model training, evaluation, and deployment Build scalable ML infrastructure and deployment pipelines Integrate ML outputs into user-facing products and backend systems Stay current with AI/ML trends and apply relevant innovations into our stack Contribute to debugging, testing, and optimization of production ML systems You'll Thrive Here If You Take full ownership - you More ❯

Project Description: We are seeking highly skilled and motivated Generative AI Engineers to join our growing AI team. You will be responsible for designing, developing, and deploying cutting-edge Generative AI solutions using LLMs, Transformers, and Diffusion models. This role involves working on enterprise-grade applications such as intelligent chatbots, document summarization, code assistants, and more. Responsibilities: Design, prototype, and … deploy Generative AI models (LLMs, Transformers, Diffusion models) for real-world enterprise use cases. Build and fine-tune LLM-based applications such as: - Chatbots - Document Q&A systems - Report generators - Code assistants - Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data … stores using Python, Java, or Node.js. Collaborate with architects to define scalable, secure, and cost-efficient AI service architectures. Implement AI/ML pipelines for training, validation, and deployment using tools like MLflow, Vertex AI, or Azure ML. Monitor model performance, detect drift, and drive continuous improvement. Optimize inference performance and cost through model compression, quantization, and API optimization. Ensure More ❯

Project Description: We are seeking highly skilled and motivated Generative AI Engineers to join our growing AI team. You will be responsible for designing, developing, and deploying cutting-edge Generative AI solutions using LLMs, Transformers, and Diffusion models. This role involves working on enterprise-grade applications such as intelligent chatbots, document summarization, code assistants, and more. Responsibilities: Design, prototype, and … deploy Generative AI models (LLMs, Transformers, Diffusion models) for real-world enterprise use cases. Build and fine-tune LLM-based applications such as: - Chatbots - Document Q&A systems - Report generators - Code assistants - Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data … stores using Python, Java, or Node.js. Collaborate with architects to define scalable, secure, and cost-efficient AI service architectures. Implement AI/ML pipelines for training, validation, and deployment using tools like MLflow, Vertex AI, or Azure ML. Monitor model performance, detect drift, and drive continuous improvement. Optimize inference performance and cost through model compression, quantization, and API optimization. Ensure More ❯

Project Description: We are seeking highly skilled and motivated Generative AI Engineers to join our growing AI team. You will be responsible for designing, developing, and deploying cutting-edge Generative AI solutions using LLMs, Transformers, and Diffusion models. This role involves working on enterprise-grade applications such as intelligent chatbots, document summarization, code assistants, and more. Responsibilities: Design, prototype, and … deploy Generative AI models (LLMs, Transformers, Diffusion models) for real-world enterprise use cases. Build and fine-tune LLM-based applications such as: - Chatbots - Document Q&A systems - Report generators - Code assistants - Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data … stores using Python, Java, or Node.js. Collaborate with architects to define scalable, secure, and cost-efficient AI service architectures. Implement AI/ML pipelines for training, validation, and deployment using tools like MLflow, Vertex AI, or Azure ML. Monitor model performance, detect drift, and drive continuous improvement. Optimize inference performance and cost through model compression, quantization, and API optimization. Ensure More ❯

Project Description: We are seeking highly skilled and motivated Generative AI Engineers to join our growing AI team. You will be responsible for designing, developing, and deploying cutting-edge Generative AI solutions using LLMs, Transformers, and Diffusion models. This role involves working on enterprise-grade applications such as intelligent chatbots, document summarization, code assistants, and more. Responsibilities: Design, prototype, and … deploy Generative AI models (LLMs, Transformers, Diffusion models) for real-world enterprise use cases. Build and fine-tune LLM-based applications such as: - Chatbots - Document Q&A systems - Report generators - Code assistants - Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data … stores using Python, Java, or Node.js. Collaborate with architects to define scalable, secure, and cost-efficient AI service architectures. Implement AI/ML pipelines for training, validation, and deployment using tools like MLflow, Vertex AI, or Azure ML. Monitor model performance, detect drift, and drive continuous improvement. Optimize inference performance and cost through model compression, quantization, and API optimization. Ensure More ❯

in multiple locations — London, Edinburgh, Newcastle, and Erskine — with the expectation to attend any of these offices when required. Project Description: We are seeking highly skilled and motivated Generative AI Engineers to join our growing AI team. You will be responsible for designing, developing, and deploying cutting-edge Generative AI solutions using LLMs, Transformers, and Diffusion models. This role involves … working on enterprise-grade applications such as intelligent chatbots, document summarization, code assistants, and more. Responsibilities: Design, prototype, and deploy Generative AI models (LLMs, Transformers, Diffusion models) for real-world enterprise use cases. Build and fine-tune LLM-based applications such as: Chatbots Document Q&A systems Report generators Code assistants Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG … and context-aware pipelines to enhance model accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data stores using Python, Java, or Node.js. Collaborate with architects to define scalable, secure, and cost-efficient AI service architectures. Implement AI/ML pipelines for training, validation, and deployment using tools like MLflow, Vertex AI, or Azure ML. Monitor model performance More ❯

Role summary: As a Principal Data Scientist (individual contributor), you will play a hands-on role in designing, building, and deploying scalable AI solutions that go beyond prototypes and are actively used in production. You'll work closely with collaborative teams to co-develop innovative products for financial markets and professionals.We're looking for someone who combines deep technical expertise … business needs and production-grade standards. What you'll be doing: This is a hands-on technical leadership role in a high-impact environment focused on delivering production-ready AI systems. Lead the end-to-end development of AI solutions: design, build, test, and deploy models that are robust, scalable, and used by real users. Apply NLP and LLM techniques … to solve real-world problems, ensuring models are optimized for performance and reliability. Continuously improve model quality through tuning, evaluation, and feedback from production usage. Evaluate third-party AI solutions with a critical eye on performance, scalability, and integration into production environments. Write and maintain production-grade Python code , adhering to best practices in software engineering and model development. Collaborate More ❯

processes, identify gaps, and implement solutions that drive efficiency and innovation. Lead migration and upgrade projects for legacy systems, ensuring minimal disruption and maximizing system adoption across teams. Leverage AI/ML and analytics capabilities to enhance reporting, forecasting, and decision-making within these platforms. Lead end-to-end digital transformation initiatives, modernizing legacy systems and migrating critical business applications … Computer Science, or related field. Certifications: PMP, Digital Leader (Azure, AWS, or Google Cloud). Technical Depth: Expertise in at least two areas: Salesforce Sales Cloud, Cloud Networking, Security, AI, Storage, Private/Hybrid/Public Cloud, Data Protection, Disaster Recovery. Industry Trends: Experience with AI/ML-driven CRM solutions and cloud-native architectures More ❯

processes, identify gaps, and implement solutions that drive efficiency and innovation. Lead migration and upgrade projects for legacy systems, ensuring minimal disruption and maximizing system adoption across teams. Leverage AI/ML and analytics capabilities to enhance reporting, forecasting, and decision-making within these platforms. Lead end-to-end digital transformation initiatives, modernizing legacy systems and migrating critical business applications … Computer Science, or related field. Certifications: PMP, Digital Leader (Azure, AWS, or Google Cloud). Technical Depth: Expertise in at least two areas: Salesforce Sales Cloud, Cloud Networking, Security, AI, Storage, Private/Hybrid/Public Cloud, Data Protection, Disaster Recovery. Industry Trends: Experience with AI/ML-driven CRM solutions and cloud-native architectures More ❯

processes, identify gaps, and implement solutions that drive efficiency and innovation. Lead migration and upgrade projects for legacy systems, ensuring minimal disruption and maximizing system adoption across teams. Leverage AI/ML and analytics capabilities to enhance reporting, forecasting, and decision-making within these platforms. Lead end-to-end digital transformation initiatives, modernizing legacy systems and migrating critical business applications … Computer Science, or related field. Certifications: PMP, Digital Leader (Azure, AWS, or Google Cloud). Technical Depth: Expertise in at least two areas: Salesforce Sales Cloud, Cloud Networking, Security, AI, Storage, Private/Hybrid/Public Cloud, Data Protection, Disaster Recovery. Industry Trends: Experience with AI/ML-driven CRM solutions and cloud-native architectures More ❯

based environments. Maintain high standards in code review, documentation, and delivery in a DevOps context. Apply a deep understanding of ML techniques, from supervised/unsupervised learning to generative AI and large language models. What We’re Looking For Essential Skills and Experience: Proven ability to solve complex, real-world problems through data science and analytics. Experience coaching and reviewing … data science efforts with broader business objectives. Desirable Skills: Experience using R and NLP or deep learning techniques (e.g. TF-IDF, word embeddings, CNNs, RNNs). Familiarity with Generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large or complex organisations More ❯

based environments. Maintain high standards in code review, documentation, and delivery in a DevOps context. Apply a deep understanding of ML techniques, from supervised/unsupervised learning to generative AI and large language models. What We’re Looking For Essential Skills and Experience: Proven ability to solve complex, real-world problems through data science and analytics. Experience coaching and reviewing … data science efforts with broader business objectives. Desirable Skills: Experience using R and NLP or deep learning techniques (e.g. TF-IDF, word embeddings, CNNs, RNNs). Familiarity with Generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large or complex organisations More ❯

based environments. Maintain high standards in code review, documentation, and delivery in a DevOps context. Apply a deep understanding of ML techniques, from supervised/unsupervised learning to generative AI and large language models. What We’re Looking For Essential Skills and Experience: Proven ability to solve complex, real-world problems through data science and analytics. Experience coaching and reviewing … data science efforts with broader business objectives. Desirable Skills: Experience using R and NLP or deep learning techniques (e.g. TF-IDF, word embeddings, CNNs, RNNs). Familiarity with Generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large or complex organisations More ❯

based environments. Maintain high standards in code review, documentation, and delivery in a DevOps context. Apply a deep understanding of ML techniques, from supervised/unsupervised learning to generative AI and large language models. What We’re Looking For Essential Skills and Experience: Proven ability to solve complex, real-world problems through data science and analytics. Experience coaching and reviewing … data science efforts with broader business objectives. Desirable Skills: Experience using R and NLP or deep learning techniques (e.g. TF-IDF, word embeddings, CNNs, RNNs). Familiarity with Generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large or complex organisations More ❯

based environments. Maintain high standards in code review, documentation, and delivery in a DevOps context. Apply a deep understanding of ML techniques, from supervised/unsupervised learning to generative AI and large language models. What We’re Looking For Essential Skills and Experience: Proven ability to solve complex, real-world problems through data science and analytics. Experience coaching and reviewing … data science efforts with broader business objectives. Desirable Skills: Experience using R and NLP or deep learning techniques (e.g. TF-IDF, word embeddings, CNNs, RNNs). Familiarity with Generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large or complex organisations More ❯

Cloud & DevOps: Experience with AWS cloud services, Terraform, Docker, Kubernetes Agile/DevOps: Experience with Agile methodologies, CI/CD pipelines, and project management tools (Jira, Confluence, Bitbucket). AI/ML: Exposure to AI/ML projects or data analytics. Benefits and Perks Our comprehensive offering is designed around flexibility, well-being, and continuous growth, ensuring that you have More ❯

Cloud & DevOps: Experience with AWS cloud services, Terraform, Docker, Kubernetes Agile/DevOps: Experience with Agile methodologies, CI/CD pipelines, and project management tools (Jira, Confluence, Bitbucket). AI/ML: Exposure to AI/ML projects or data analytics. Benefits and Perks Our comprehensive offering is designed around flexibility, well-being, and continuous growth, ensuring that you have More ❯

Cloud & DevOps: Experience with AWS cloud services, Terraform, Docker, Kubernetes Agile/DevOps: Experience with Agile methodologies, CI/CD pipelines, and project management tools (Jira, Confluence, Bitbucket). AI/ML: Exposure to AI/ML projects or data analytics. Benefits and Perks Our comprehensive offering is designed around flexibility, well-being, and continuous growth, ensuring that you have More ❯

Cloud & DevOps: Experience with AWS cloud services, Terraform, Docker, Kubernetes Agile/DevOps: Experience with Agile methodologies, CI/CD pipelines, and project management tools (Jira, Confluence, Bitbucket). AI/ML: Exposure to AI/ML projects or data analytics. Benefits and Perks Our comprehensive offering is designed around flexibility, well-being, and continuous growth, ensuring that you have More ❯

Cloud & DevOps: Experience with AWS cloud services, Terraform, Docker, Kubernetes Agile/DevOps: Experience with Agile methodologies, CI/CD pipelines, and project management tools (Jira, Confluence, Bitbucket). AI/ML: Exposure to AI/ML projects or data analytics. Benefits and Perks Our comprehensive offering is designed around flexibility, well-being, and continuous growth, ensuring that you have More ❯