576 to 600 of 1,743 Remote Machine Learning Jobs

AI/ML Engineer Applied AI for Real-World Impact Location: Nottingham (Hybrid 2 days per week on-site) The Opportunity Join a fast-growing AI company spun out from world-class academic research and now partnering with leading brands like Boots . Youll design, build, and scale intelligent systems that make a real-world difference across healthcare, mobility, and … retail, transforming cutting-edge machine learning into production-ready solutions that reach millions. Youll work end-to-end across the ML lifecycle, from experimentation and data pipelines to deployment and monitoring, helping shape how AI moves from research into real-world impact. What Youll Do Design, implement, and optimise ML models for large-scale behavioural and temporal datasets … Build and maintain robust, cloud-based data and model pipelines Deploy, monitor, and iterate on production ML systems (forecasting, classification, behavioural modelling) Collaborate with data scientists, software engineers, and product teams to deliver scalable, explainable AI solutions Contribute to MLOps best practices , experimentation frameworks, and model governance Why Join Work with a modern AI/ML stack (Python, SQL, Databricks More ❯

coverage and quality of APIs, tooling, and providers in the upstream Llama Stack project. In this role, you'll contribute directly to Red Hat's rapidly growing AI/ML family of products and will be responsible for the design, development, and refinement of software that enables the creation and deployment of generative AI models.The ideal candidate will have a … proven background in developing and testing robust and scalable Python solutions within an AI/ML context. As part of your responsibilities, you will need to adhere to coding best practices and standards, including well-documented, and efficient code; building and implementing upstream unit and E2E automated tests, maintaining updated code documentation and comments, following security best practices, participating in … end-to-end tests to guarantee the reliability and performance in the upstream project, maintaining CI/CD workflows in GitHub, and ensuring downstream quality. Create robust AI/ML software tools to enable AI Application development and contribute to a healthy open source community. Participate in AI-assisted code reviews, utilizing tools that provide real-time feedback, identify potential More ❯

AI/ML Engineer – Applied AI for Real-World Impact Location: Nottingham (Hybrid – 2 days per week on-site) The Opportunity Join a fast-growing AI company spun out from world-class academic research and now partnering with leading brands like Boots . You’ll design, build, and scale intelligent systems that make a real-world difference across healthcare, mobility … and retail, transforming cutting-edge machine learning into production-ready solutions that reach millions. You’ll work end-to-end across the ML lifecycle, from experimentation and data pipelines to deployment and monitoring, helping shape how AI moves from research into real-world impact. What You’ll Do Design, implement, and optimise ML models for large-scale behavioural … and temporal datasets Build and maintain robust, cloud-based data and model pipelines Deploy, monitor, and iterate on production ML systems (forecasting, classification, behavioural modelling) Collaborate with data scientists, software engineers, and product teams to deliver scalable, explainable AI solutions Contribute to MLOps best practices , experimentation frameworks, and model governance Why Join Work with a modern AI/ML stack More ❯

AI/ML Engineer – Applied AI for Real-World Impact Location: Nottingham (Hybrid – 2 days per week on-site) The Opportunity Join a fast-growing AI company spun out from world-class academic research and now partnering with leading brands like Boots . You’ll design, build, and scale intelligent systems that make a real-world difference across healthcare, mobility … and retail, transforming cutting-edge machine learning into production-ready solutions that reach millions. You’ll work end-to-end across the ML lifecycle, from experimentation and data pipelines to deployment and monitoring, helping shape how AI moves from research into real-world impact. What You’ll Do Design, implement, and optimise ML models for large-scale behavioural … and temporal datasets Build and maintain robust, cloud-based data and model pipelines Deploy, monitor, and iterate on production ML systems (forecasting, classification, behavioural modelling) Collaborate with data scientists, software engineers, and product teams to deliver scalable, explainable AI solutions Contribute to MLOps best practices , experimentation frameworks, and model governance Why Join Work with a modern AI/ML stack More ❯

AI/ML Engineer – Applied AI for Real-World Impact Location: Nottingham (Hybrid – 2 days per week on-site) The Opportunity Join a fast-growing AI company spun out from world-class academic research and now partnering with leading brands like Boots . You’ll design, build, and scale intelligent systems that make a real-world difference across healthcare, mobility … and retail, transforming cutting-edge machine learning into production-ready solutions that reach millions. You’ll work end-to-end across the ML lifecycle, from experimentation and data pipelines to deployment and monitoring, helping shape how AI moves from research into real-world impact. What You’ll Do Design, implement, and optimise ML models for large-scale behavioural … and temporal datasets Build and maintain robust, cloud-based data and model pipelines Deploy, monitor, and iterate on production ML systems (forecasting, classification, behavioural modelling) Collaborate with data scientists, software engineers, and product teams to deliver scalable, explainable AI solutions Contribute to MLOps best practices , experimentation frameworks, and model governance Why Join Work with a modern AI/ML stack More ❯

AI/ML Engineer – Applied AI for Real-World Impact Location: Nottingham (Hybrid – 2 days per week on-site) If you think you are the right match for the following opportunity, apply after reading the complete description. The Opportunity Join a fast-growing AI company spun out from world-class academic research and now partnering with leading brands like Boots. … world difference across healthcare, mobility, and retail, transforming cutting-edge machine learning into production-ready solutions that reach millions. You'll work end-to-end across the ML lifecycle, from experimentation and data pipelines to deployment and monitoring, helping shape how AI moves from research into real-world impact. What You'll Do Design, implement, and optimise ML … models for large-scale behavioural and temporal datasets Build and maintain robust, cloud-based data and model pipelines Deploy, monitor, and iterate on production ML systems (forecasting, classification, behavioural modelling) Collaborate with data scientists, software engineers, and product teams to deliver scalable, explainable AI solutions Contribute to MLOps best practices, experimentation frameworks, and model governance Why Join Work with a More ❯

large datasets. Technical Skills Proficiency in cloud computing and python programming. Familiarity with Python libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linear algebra principles for modelling and optimisation. Calculus for optimising algorithms and models. Predictive modelling techniques for regression and classification. … Time series analysis for handling time-dependant data. Deep learning and neural networks. LLM Operations Expertise in managing and operationalising large language models. Experience in deploying models on cloud platforms (e.g. AWS, Sage maker, Google AI Platform, IBM Watson) IND_PC3 More ❯

large datasets. Technical Skills Proficiency in cloud computing and python programming. Familiarity with Python libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linear algebra principles for modelling and optimisation. Calculus for optimising algorithms and models. Predictive modelling techniques for regression and classification. … Time series analysis for handling time-dependant data. Deep learning and neural networks. LLM Operations Expertise in managing and operationalising large language models. Experience in deploying models on cloud platforms (e.g. AWS, Sage maker, Google AI Platform, IBM Watson) IND_PC3 More ❯

large datasets. Technical Skills Proficiency in cloud computing and python programming. Familiarity with Python libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linear algebra principles for modelling and optimisation. Calculus for optimising algorithms and models. Predictive modelling techniques for regression and classification. … Time series analysis for handling time-dependant data. Deep learning and neural networks. LLM Operations Expertise in managing and operationalising large language models. Experience in deploying models on cloud platforms (e.g. AWS, Sage maker, Google AI Platform, IBM Watson) IND_PC3 More ❯

large datasets. Technical Skills Proficiency in cloud computing and python programming. Familiarity with Python libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linear algebra principles for modelling and optimisation. Calculus for optimising algorithms and models. Predictive modelling techniques for regression and classification. … Time series analysis for handling time-dependant data. Deep learning and neural networks. LLM Operations Expertise in managing and operationalising large language models. Experience in deploying models on cloud platforms (e.g. AWS, Sage maker, Google AI Platform, IBM Watson) IND_PC3 More ❯

large datasets. Technical Skills Proficiency in cloud computing and python programming. Familiarity with Python libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linear algebra principles for modelling and optimisation. Calculus for optimising algorithms and models. Predictive modelling techniques for regression and classification. … Time series analysis for handling time-dependant data. Deep learning and neural networks. LLM Operations Expertise in managing and operationalising large language models. Experience in deploying models on cloud platforms (e.g. AWS, Sage maker, Google AI Platform, IBM Watson) IND_PC3 More ❯

large datasets. Technical Skills Proficiency in cloud computing and python programming. Familiarity with Python libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linear algebra principles for modelling and optimisation. Calculus for optimising algorithms and models. Predictive modelling techniques for regression and classification. … Time series analysis for handling time-dependant data. Deep learning and neural networks. LLM Operations Expertise in managing and operationalising large language models. Experience in deploying models on cloud platforms (e.g. AWS, Sage maker, Google AI Platform, IBM Watson) IND_PC3 More ❯

large datasets. Technical Skills Proficiency in cloud computing and python programming. Familiarity with Python libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linear algebra principles for modelling and optimisation. Calculus for optimising algorithms and models. Predictive modelling techniques for regression and classification. … Time series analysis for handling time-dependant data. Deep learning and neural networks. LLM Operations Expertise in managing and operationalising large language models. Experience in deploying models on cloud platforms (e.g. AWS, Sage maker, Google AI Platform, IBM Watson) IND_PC3 More ❯

when the right vacancy comes along. The Data & Science Org At Deliveroo we have an outstanding data science organisation, with a mission to enable the highest quality human and machine decision-making. We work throughout the company - in product, business and platform teams - using analysis, experimentation, causal inference and machine learning techniques. We are uniquely placed to … working from home and a parent-friendly working culture Access to free mortgage advice Cycle to Work Scheme or Season Ticket Loans, depending how you wish to travel Excellent learning and development opportunities and access to RooLearn, our learning platform, packed with high quality training and content Regular Employee Resource Group (ERG) led social events - examples include dinners More ❯

ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/CD, Docker, AWS (S3, Lambda, SageMaker), Kubernetes, Terraform/CDK ML Ops & Automation: MLFlow, feature stores, model monitoring, A/B testing Data Security & Compliance: Secure SDLC, ISO/NIST, data governance, GDPR-compliant pipelines Proven delivery of data science models … Security data environments. Security Clearance: Military background (RAF, Army, Navy) or MOD/National Security project experience. Experience with Palantir Foundry (full training provided). Familiarity with AI/ML Ops pipelines , real-time analytics, or edge deployments. Big Data stack knowledge (e.g., AWS Bedrock, LangChain). Work on projects where data-driven decisions have real-world consequences. training & leadership … opportunities. Tech & training: Palantir certification & AI/ML training included. Trajectory: Series A-funded, one of the fastest-growing UK tech start-ups in defence data analytics. Compensation & benefits Bonus: Up to 15% Pension: Holidays: Generous allowance + bank holidays Birthday off: Yes Healthcare: Private medical AI/ML training & certifications More ❯

and governance, while helping shape a platform-as-a-product mindset. Key responsibilities include: Building and maintaining data infrastructure: Develop microservices, pipelines, and backend systems that power analytics and machine learning initiatives. Driving platform evolution: Design and implement scalable, secure, and efficient data services using tools such as Terraform, Docker, and AWS. Data governance and observability: Introduce and … enhance tooling for data lineage, contracts, monitoring, and cataloguing. Operational excellence: Lead automation, monitoring, and incident response to maintain high platform reliability. Cross-functional collaboration: Work with data scientists, ML engineers, analysts, and product teams to understand and meet their data needs. Mentorship and culture: Support the growth of peers through knowledge sharing and by championing engineering best practices. YOUR More ❯

and governance, while helping shape a platform-as-a-product mindset. Key responsibilities include: Building and maintaining data infrastructure: Develop microservices, pipelines, and backend systems that power analytics and machine learning initiatives. Driving platform evolution: Design and implement scalable, secure, and efficient data services using tools such as Terraform, Docker, and AWS. Data governance and observability: Introduce and … enhance tooling for data lineage, contracts, monitoring, and cataloguing. Operational excellence: Lead automation, monitoring, and incident response to maintain high platform reliability. Cross-functional collaboration: Work with data scientists, ML engineers, analysts, and product teams to understand and meet their data needs. Mentorship and culture: Support the growth of peers through knowledge sharing and by championing engineering best practices. YOUR More ❯

and governance, while helping shape a platform-as-a-product mindset. Key responsibilities include: Building and maintaining data infrastructure: Develop microservices, pipelines, and backend systems that power analytics and machine learning initiatives. Driving platform evolution: Design and implement scalable, secure, and efficient data services using tools such as Terraform, Docker, and AWS. Data governance and observability: Introduce and … enhance tooling for data lineage, contracts, monitoring, and cataloguing. Operational excellence: Lead automation, monitoring, and incident response to maintain high platform reliability. Cross-functional collaboration: Work with data scientists, ML engineers, analysts, and product teams to understand and meet their data needs. Mentorship and culture: Support the growth of peers through knowledge sharing and by championing engineering best practices. YOUR More ❯

to make an impact that matters, through challenging projects which demand ambitious innovation and thought leadership. Build strong relationships with a diverse range of stakeholders. Gain access to endless learning opportunities. Work closely with the range of teams within the business to bring products to life. The Role As a Principal Data Engineer, you will be responsible for the … solutions. Drive continuous improvement in engineering processes to enhance efficiency, production stability, and ROI. Manage and own the technical debt process, ensuring long-term maintainability and scalability. Collaborate with ML and GenAI teams to operationalize models into production pipelines. Ensure observability, data quality, lineage, and governance across the data lifecycle. Mentor and lead a team of engineers, fostering a culture … and orchestration tools Expertise in data integration patterns, ETL/ELT, and data pipeline orchestration Experience with data quality frameworks, metadata management, and data lineage Hands-on experience with machine learning pipelines and generative AI engineering Familiarity with DevOps practices, CI/CD for data workflows, and infrastructure-as-code (e.g., Terraform, CloudFormation). Proven track record of More ❯

to make an impact that matters, through challenging projects which demand ambitious innovation and thought leadership. Build strong relationships with a diverse range of stakeholders. Gain access to endless learning opportunities. Work closely with the range of teams within the business to bring products to life. The Role As a Principal Data Engineer, you will be responsible for the … solutions. Drive continuous improvement in engineering processes to enhance efficiency, production stability, and ROI. Manage and own the technical debt process, ensuring long-term maintainability and scalability. Collaborate with ML and GenAI teams to operationalize models into production pipelines. Ensure observability, data quality, lineage, and governance across the data lifecycle. Mentor and lead a team of engineers, fostering a culture … and orchestration tools Expertise in data integration patterns, ETL/ELT, and data pipeline orchestration Experience with data quality frameworks, metadata management, and data lineage Hands-on experience with machine learning pipelines and generative AI engineering Familiarity with DevOps practices, CI/CD for data workflows, and infrastructure-as-code (e.g., Terraform, CloudFormation). Proven track record of More ❯

to make an impact that matters, through challenging projects which demand ambitious innovation and thought leadership. Build strong relationships with a diverse range of stakeholders. Gain access to endless learning opportunities. Work closely with the range of teams within the business to bring products to life. The Role As a Principal Data Engineer, you will be responsible for the … solutions. Drive continuous improvement in engineering processes to enhance efficiency, production stability, and ROI. Manage and own the technical debt process, ensuring long-term maintainability and scalability. Collaborate with ML and GenAI teams to operationalize models into production pipelines. Ensure observability, data quality, lineage, and governance across the data lifecycle. Mentor and lead a team of engineers, fostering a culture … and orchestration tools Expertise in data integration patterns, ETL/ELT, and data pipeline orchestration Experience with data quality frameworks, metadata management, and data lineage Hands-on experience with machine learning pipelines and generative AI engineering Familiarity with DevOps practices, CI/CD for data workflows, and infrastructure-as-code (e.g., Terraform, CloudFormation). Proven track record of More ❯

to make an impact that matters, through challenging projects which demand ambitious innovation and thought leadership. Build strong relationships with a diverse range of stakeholders. Gain access to endless learning opportunities. Work closely with the range of teams within the business to bring products to life. The Role As a Principal Data Engineer, you will be responsible for the … solutions. Drive continuous improvement in engineering processes to enhance efficiency, production stability, and ROI. Manage and own the technical debt process, ensuring long-term maintainability and scalability. Collaborate with ML and GenAI teams to operationalize models into production pipelines. Ensure observability, data quality, lineage, and governance across the data lifecycle. Mentor and lead a team of engineers, fostering a culture … and orchestration tools Expertise in data integration patterns, ETL/ELT, and data pipeline orchestration Experience with data quality frameworks, metadata management, and data lineage Hands-on experience with machine learning pipelines and generative AI engineering Familiarity with DevOps practices, CI/CD for data workflows, and infrastructure-as-code (e.g., Terraform, CloudFormation). Proven track record of More ❯

to make an impact that matters, through challenging projects which demand ambitious innovation and thought leadership. Build strong relationships with a diverse range of stakeholders. Gain access to endless learning opportunities. Work closely with the range of teams within the business to bring products to life. The Role As a Principal Data Engineer, you will be responsible for the … solutions. Drive continuous improvement in engineering processes to enhance efficiency, production stability, and ROI. Manage and own the technical debt process, ensuring long-term maintainability and scalability. Collaborate with ML and GenAI teams to operationalize models into production pipelines. Ensure observability, data quality, lineage, and governance across the data lifecycle. Mentor and lead a team of engineers, fostering a culture … and orchestration tools Expertise in data integration patterns, ETL/ELT, and data pipeline orchestration Experience with data quality frameworks, metadata management, and data lineage Hands-on experience with machine learning pipelines and generative AI engineering Familiarity with DevOps practices, CI/CD for data workflows, and infrastructure-as-code (e.g., Terraform, CloudFormation). Proven track record of More ❯

to make an impact that matters, through challenging projects which demand ambitious innovation and thought leadership. Build strong relationships with a diverse range of stakeholders. Gain access to endless learning opportunities. Work closely with the range of teams within the business to bring products to life. The Role As a Principal Data Engineer, you will be responsible for the … solutions. Drive continuous improvement in engineering processes to enhance efficiency, production stability, and ROI. Manage and own the technical debt process, ensuring long-term maintainability and scalability. Collaborate with ML and GenAI teams to operationalize models into production pipelines. Ensure observability, data quality, lineage, and governance across the data lifecycle. Mentor and lead a team of engineers, fostering a culture … and orchestration tools Expertise in data integration patterns, ETL/ELT, and data pipeline orchestration Experience with data quality frameworks, metadata management, and data lineage Hands-on experience with machine learning pipelines and generative AI engineering Familiarity with DevOps practices, CI/CD for data workflows, and infrastructure-as-code (e.g., Terraform, CloudFormation). Proven track record of More ❯

to make an impact that matters, through challenging projects which demand ambitious innovation and thought leadership. Build strong relationships with a diverse range of stakeholders. Gain access to endless learning opportunities. Work closely with the range of teams within the business to bring products to life. The Role As a Principal Data Engineer, you will be responsible for the … solutions. Drive continuous improvement in engineering processes to enhance efficiency, production stability, and ROI. Manage and own the technical debt process, ensuring long-term maintainability and scalability. Collaborate with ML and GenAI teams to operationalize models into production pipelines. Ensure observability, data quality, lineage, and governance across the data lifecycle. Mentor and lead a team of engineers, fostering a culture … and orchestration tools Expertise in data integration patterns, ETL/ELT, and data pipeline orchestration Experience with data quality frameworks, metadata management, and data lineage Hands-on experience with machine learning pipelines and generative AI engineering Familiarity with DevOps practices, CI/CD for data workflows, and infrastructure-as-code (e.g., Terraform, CloudFormation). Proven track record of More ❯