401 to 425 of 1,141 Permanent Machine Learning Jobs

including version control, testing, and CI/CD. Nice to Have Familiarity with Google Cloud Platform (GCP). Bonus points for experience with AI, Machine Learning (PyTorch/TensorFlow), LLM frameworks (MCP/Langchain), or scientific Python (NumPy/Pandas)—though this is absolutely not necessary to apply. ...

/best practices and practical experience applying TDD. clear communication/interpersonal skills are a must for working closely with internal teams. Experience with Machine Learning, CI/CD and IAC using Terraform for management of Azure/AWS would be beneficial. What you'll get in return ...

Kubernetes. Familiarity with event-driven architecture and message brokers (e.g., Kafka, RabbitMQ). Knowledge of front-end performance optimisation and accessibility standards. Exposure to machine learning pipelines or data engineering workflows. Prior experience working in startup environments or high-growth technology companies. Benefits Hybrid working as standard ...

these processes to link datasets, develop ETL pipelines and identify transactions of potential concern Has an understanding of advanced data science techniques such as machine learning, natural language processing and statistical analysis. Has experience of using data visualisation tools such as PowerBI Has experience with general ledger/ ...

paced environment Python Linux/PuTTY Understanding of Firewalls and IT Security Nice to Have Skills: Language Skills, especially French and German AI Skills; Machine Learning, Agents Data Science Skills; R, statistical analyses ...

financial services Hands-on development: X++, C#, Python, T-SQL, PowerFX, PowerShell Source control and containerization: TFVC, Git, Docker Tools: Azure IPAAS, Azure ML, Dataverse, PowerApps, Power Automate, SQL Server Administration, Fabric, Kafka, Copilot Studio, Azure AI Services, Ollama Integration: REST/SOAP APIs, solution performance analysis Functional knowledge ...

Innovation Software Engineer (Numerical Modelling, AI/ML, C++/Python) Guildford, Surrey (On-site) £65000 - £100,000 + 25% Bonus, 10% Pension, Private Medical. - A Masters or PhD Degree in Computing or STEM disciplines. - Can work full-time, 5 days a week in Guildford in the office. Your … high-level scientific language (e.g., Python, Julia). We are particularly looking at experience with scientific computing, numerical methods, or computational modelling. Desirables are Machine learning, optimization, control, probabilistic modelling, or related fields. Familiarity digital twins, agentic systems, reinforcement learning or advanced optimisation. What ...

Support early-stage engagements as well as full lifecycle delivery What we’re looking for Proven experience designing and/or building AI/ML solutions in enterprise environments Strong hands-on experience with Generative AI and LLMs (selection, fine-tuning, deployment) Experience with at least two of the following … platforms : AWS (Bedrock/SageMaker) Azure (Azure ML/OpenAI) Google Cloud (Vertex AI) OpenAI APIs Solid understanding of machine learning, data engineering, and big data concepts Experience designing cloud-native architectures and scalable systems Ability to bridge business requirements and technical solutions Understanding of security, governance ...

Fraud Operations Director in Fintech, you will work in a highly collaborative environment with extensive amounts of data to research and develop deep learning models to solve real-world problems and apply them to tasks such as identifying bad actors, preventing fraud, building anomaly detection models, and analytics … perform shared goals. Successful outcomes in this role will significantly impact the business. Responsibilities: Lead the development and optimization of fraud detection systems using machine learning and rule-based engines. Work closely with management, product, engineering, compliance, legal, and security teams to align, present, and implement ...

front-end interfaces using frameworks like Vue.js or React, to present complex datasets and user workflows. • Collaborate with data scientists and engineers to integrate ML models, ETL pipelines, and cloud-based data storage solutions. • Optimise system performance and reliability for high-volume data operations across distributed environments. • Implement secure, compliant … DevOps practices including TDD, CI/CD and infrastructure as code. • Experience of optimising systems for performance and scalability and reliability. • Understanding of machine learning workflows or MLOps for deploying and monitoring models in production. • Experience with cloud platforms, especially AWS and its data services (e.g., BigQuery, Redshift ...

site selection event on 5 May 2026. Desired Skills and Experience: Experience with ReactJS. Familiarity with geospatial data science or remote sensing. Knowledge of machine learning techniques and automation workflows. Interest in energy markets, commodities trading or environmental analytics. Exposure to satellite imagery analysis, AI applications or alternative … your development. You’ll also benefit from: Full‐time, hands‐on experience working directly with one of our leading clients Access to the Udemy learning platform Ongoing support and regular check‐ins from the Aubay team The potential to be considered for a future direct role with the client ...

intelligence and agent-based systems Agent-based simulation and middleware platforms for multi-agent systems AI-driven forecasting and flexibility orchestration Scalable data and machine learning pipelines Digital twin architectures for cyber-physical energy systems AI-based energy system modeling, simulation, and optimization Secure and interoperable infrastructure architectures … Denmark was established to create value for and with society. Whether our contributions come in the form of excellent research, innovative solutions, education or learning, we must make a positive difference to society and contribute to a sustainable future . click apply for full job details ...

delivery of complex AI projects across global teams Mentor engineers and data scientists and drive best practice Key requirements Strong background in AI, machine learning or data science Deep experience with LLMs and modern GenAI frameworks Experience designing AI architectures such as RAG and agent-based systems Strong ...

analytical data processing Experience working with non-relational or semi-structured data sources Understanding of modern data modelling for analytics and reporting Awareness of machine learning workflows or advanced analytics use cases Understanding of networking, security and access control within AWS or Azure Awareness of data governance ...

/best practices and practical experience applying TDD. clear communication/interpersonal skills are a must for working closely with internal teams. Experience with Machine Learning, CI/CD and IAC using Terraform for management of Azure/AWS would be beneficial. What you'll get in return ...

Java/J2EE architectural skills Deep data analytic skills or data scientist. Hands on experience on cutting edge applications of Predictive analytics and Machine learning Hands on experience on development of QA Dashboard with Angular JS, Springboot and MongoDB Create data by utilizing test data tools to setup ...

love using data to tell a story. We’re also the world’s largest team of data scientists, data engineers, and experts in machine learning and AI. Our focus is on big problems using the latest tech, serious brain power, and deep knowledge of just about every industry. ...

bids Technology environment You don’t need to know everything, but experience across areas such as: • Azure data ecosystem (Data Factory, Synapse, Databricks, Azure ML, Azure OpenAI) • Power BI • SQL Server • Cloud data architectures • API/integration design Nice to have exposure to: • Microsoft Fabric • Multi-cloud environments (AWS/ ...

publications showcasing real-world problem-solving Expert Python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels) Deep understanding of statistical analysis, ML algorithms, and practical applications Expert-level SQL and database operations Experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases) Understanding of MLOps practices and model ...

microservices, and backend systems. Solid understanding of software architecture, cloud infrastructure (AWS and/or Azure), and modern DevOps practices. Hands-on experience integrating ML models into production systems (LLMs via APIs, fine-tuning, RAG, embeddings, agents). Ability to move fast without compromising on code quality, testing, and operational ...

business stakeholders to accelerate value realisation across complex technology estates. Key Responsibilities AI Engineering & Delivery Design, build, and deploy production‐grade AI/ML solutions , including: LLM‐enabled applications (RAG, agents, copilots) Predictive models and intelligent automation AI services embedded into modernised platforms Own end‐to‐end AI lifecycle : discovery ...

major features, platforms, and technical initiatives Collaborate with technical leads and DevOps on system scalability, performance, and reliability Ensure data platforms are AI/ML-ready, with scalable infrastructure and clean, well-structured data pipelines Collaborate with data science and analytics teams to enable model deployment, automation, and MLOps best ...

/JS Backend: R6, golem, plumber APIs Data: MariaDB (AWS RDS), S3, SQL optimization DevOps: GitHub Actions, Heroku, Digital Ocean, Docker, Git AI/ML: LLM APIs (OpenAI, Claude, etc.), ellmer package, Python LLM tooling, AI Agents Why SUSNEO? Innovation at Scale: Work on production applications that combine robust data ...

security best practices, monitoring, and incident response. Familiarity with DevSecOps and compliance frameworks (ISO 27001, SOC 2, GDPR). Exposure to big data processing, ML pipelines, or simulation workflows. Bonus: Existing interest in data science and simulation workflows in the manufacturing, energy or chemical process industries; Experience with high-performance ...

building real-world applications that incorporate large language models, agent based systems, and cloud based AI services. The role requires someone who enjoys experimenting, learning quickly, and applying new technologies in practical ways. Responsibilities: Design, develop, and deploy AI-enabled solutions using modern full stack technologies Integrate cloud-based … services (e.g. language models, machine learning, search, and cognitive APIs) into production systems Build and enhance features powered by large language models, including agent-style workflows and contextual integrations Work closely with clients to gather requirements and translate them into functional software solutions Contribute to technical discovery, prototyping ...