51 to 75 of 588 Remote/Hybrid Machine Learning Jobs

then implementing them into scalable production software, rather than purely research-focused individuals. We are looking for someone with significant commercial experience in AI, machine learning or software engineering environments. You will work on a broad range of AI challenges spanning multimodal AI, machine learning, computer … from a top university is advantageous Achieved AAA at A Level or international equivalent Proven commercial experience in software engineering, AI engineering, machine learning or closely related areas Strong programming ability with confidence in quickly learning new technologies and languages. While the role currently uses Go, Kotlin ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

portfolio (formerly Onfido) powers document and biometric verification, fraud detection, and identity decisions at global scale. From detecting deepfakes to enabling seamless onboarding, our ML systems sit directly on the critical path of digital trust—used by banks, fintechs, marketplaces, and enterprises worldwide. About the Team: You’ll join … working at the intersection of machine learning, product, and real-world constraints. The team is supported by a state-of-the-art ML Ops ecosystem (AWS, Encord, Ray, PyTorch Lightning, Weights & Biases) and partners closely with product and engineering to ship models into production at scale. This ...

quarter. What You’ll Do? Design and help develop systems that serve recommendations to over 200 million users. Drive ML roadmap creation and execution, specifically around feed ranking and recall-oriented candidate generation systems. Provide technical guidance in ML model formulation, implementation, and experimentation, and take end-to-end ownership … ML systems and key user satisfaction-based metrics. Drive architectural strategy and design for complex ML systems that support the needs of users, creators, and content stakeholders. Who are you? 8+ years of professional experience in software engineering focused on deploying machine learning models in production at scale. ...

Data Scientist (ML Engineer) Location: Manchester Salary: £49,387 to £56,515 per annum Vacancy Type: Permanent, Full Time The closing date is 18 June 2026 Job summary Do you want to do meaningful work that makes a genuine difference to society? Our main purpose here at The National Institute … should we receive sufficient applications, so please don't delay your submission. Main duties of the job We're looking for a Data Scientist (ML Engineer) to help NICE apply machine learning and advanced analytics to real world health and care challenges. Working within the Architecture & Data team ...

Data Scientist (ML Engineer) Salary: £49,387 - £56,515 per annum Location: Manchester Vacancy Type: Permanent Closing date: 18/06/2026 The National Institute for Health and Care Excellence (NICE) is the independent organisation responsible for providing national guidance and advice on promoting high quality health, public health … should we receive sufficient applications, so please don’t delay your submission. Main duties of the job We’re looking for a Data Scientist (ML Engineer) to help NICE apply machine learning and advanced analytics to real world health and care challenges. Working within the Architecture & Data team ...

Active SC required We're hiring an experienced SC-cleared Data Scientist to support a high-profile central government programme delivering advanced analytics and machine-learning solutions. This role is focused on turning complex datasets into predictive insight and deployable models that directly inform policy and operational decision … understanding of machine-learning techniques (supervised, unsupervised, model evaluation) Experience with MLOps practices, including: Model versioning and deployment CI/CD for ML workflows Monitoring and performance management Experience working with cloud-based data platforms ( AWS and/or Azure ) Strong statistical knowledge and ability to explain complex ...

Data Scientist, London/Oxford hybrid working Are you excited by the opportunity to use machine learning, NLP, and generative AI to help researchers discover knowledge faster and make better decisions? Would you enjoy turning complex scientific and business challenges into practical, production-ready AI solutions that create … strive to maintain. Our team values trust, respect, collaboration, agility, and quality. About the Role In this role, you will design and build machine learning, NLP, and generative AI solutions that support scientific discovery, knowledge extraction, decision support, and intelligent content understanding. You will work with large-scale ...

role of patents in providing a window into who is leading technology innovation, where, and at what pace. By harnessing the latest advances in machine learning combined with expert analysis, LexisNexis Intellectual Property is transforming how actionable insights are extracted from patent data. Information can now be accessed … aspects of the delivery process - from scoping support through to project delivery. The primary responsibility of this role will be the training of machine learning classifiers using patent data across a variety of technologies and industries. This supervised learning process is conducted using the proprietary LexisNexis Classification ...

Data Scientist (Python/SQL/AI & Machine Learning) Location: Newcastle Upon Tyne | Hybrid Salary: Competitive + Excellent Benefits Type: Full-time, Permanent Overview A leading financial technology and investment business is looking to appoint a Data Scientist to join its growing data and analytics function. This … portfolio analysis and business performance. Working alongside data engineers, analysts and business stakeholders, you will contribute to the development of modern analytical solutions using machine learning, AI and statistical techniques within a well-governed and evolving data environment. Key Responsibilities • Deliver end-to-end analytics solutions from data ...

years, placing 4 people with them, and all 4 are still with the company. Our client is a rapidly growing AI and Machine Learning company, specialising in the research, development and deployment of advanced technology into Defence, security, intelligence and adjacent sectors. Their team includes highly experienced software … developers, data scientists, Machine Learning specialists and researchers, with strong academic, research and Defence backgrounds. They are now looking for a Senior Business Development Manager in Defence to join their senior team and help drive their next phase of growth. This is an excellent opportunity for an experienced ...

datasets, with applications spanning molecular generation, protein representation learning, and uncertainty-aware prediction systems. This role is ideal for someone excited by frontier ML research but equally passionate about building robust, production-grade systems. You’ll Be Working On Developing large-scale foundation models for biological and chemical data … Building probabilistic ML systems capable of uncertainty estimation and Bayesian inference Training transformer architectures and latent variable models across molecular and genomic datasets Scaling distributed GPU training pipelines for multi-billion parameter models Working on generative modelling approaches for molecule and protein design Designing evaluation frameworks for biological plausibility, calibration ...