876 to 900 of 1,057 Remote/Hybrid CI/CD Jobs

person) 2+ years work experience working with modernisation patterns — containerisation, microservices, and the like 2+ years work experience working with CI / CD and deployment best practices across multiple environments (AWS-native tooling preferred) 1+ year’s work experience designing and building serverless solutions (Lambda … team skillsets Experience migrating on-premise environments to AWS Comfortable managing multiple projects and priorities simultaneously Experience (Desirable) AWS Specialty certification Experience with ML / AI services (SageMaker, AWS AI services) Familiarity with on-premise environments (hypervisors, storage, backup vendors) Scripting ability, preferably Python Benefits: 34 Days Annual Leave ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and" appropriate use "of data." Define advanced experimental designs, lead A / B testing, develop and" maintain "metrics and dashboards," establish "robust" MLOps "practices, and own"end-to-end" productionisation "from data ingestion through deployment and ongoing … extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML / DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and" appropriate use "of data." Define advanced experimental designs, lead A / B testing, develop and" maintain "metrics and dashboards," establish "robust" MLOps "practices, and own"end-to-end" productionisation "from data ingestion through deployment and ongoing … extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML / DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and" appropriate use "of data." Define advanced experimental designs, lead A / B testing, develop and" maintain "metrics and dashboards," establish "robust" MLOps "practices, and own"end-to-end" productionisation "from data ingestion through deployment and ongoing … extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML / DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and" appropriate use "of data." Define advanced experimental designs, lead A / B testing, develop and" maintain "metrics and dashboards," establish "robust" MLOps "practices, and own"end-to-end" productionisation "from data ingestion through deployment and ongoing … extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML / DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and" appropriate use "of data." Define advanced experimental designs, lead A / B testing, develop and" maintain "metrics and dashboards," establish "robust" MLOps "practices, and own"end-to-end" productionisation "from data ingestion through deployment and ongoing … extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML / DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and" appropriate use "of data." Define advanced experimental designs, lead A / B testing, develop and" maintain "metrics and dashboards," establish "robust" MLOps "practices, and own"end-to-end" productionisation "from data ingestion through deployment and ongoing … extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML / DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and" appropriate use "of data." Define advanced experimental designs, lead A / B testing, develop and" maintain "metrics and dashboards," establish "robust" MLOps "practices, and own"end-to-end" productionisation "from data ingestion through deployment and ongoing … extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML / DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and" appropriate use "of data." Define advanced experimental designs, lead A / B testing, develop and" maintain "metrics and dashboards," establish "robust" MLOps "practices, and own"end-to-end" productionisation "from data ingestion through deployment and ongoing … extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML / DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI / ...

Understanding of database design, ideally PostgreSQL Exposure to event-driven or queue-based systems (e.g. Kafka) Experience with testing practices and CI / CD pipelines Familiarity with Agile development practices Why Join: Opportunity to work in a high-impact, product-focused environment Exposure to complex … role, please feel free to reach out to Eve Geddis directly on LinkedIn. Skills: Java Spring AWS PostgreSQL Kafka Benefits: Medical Aid / Health Care Pension JBLE1 ...

data, security, and engineering teams Tech Environment Microsoft Azure (App Services, Functions, Service Bus, APIM) SQL Server Enterprise integration platforms & APIs CI / CD pipelines & DevOps practices Modern enterprise architecture tooling Experience with legal platforms such as iManage, Aderant, Intapp (or similar enterprise systems … complex enterprise environments Excellent communication and stakeholder management skills Ability to clearly explain technical solutions to non-technical audiences Experience working in Agile / DevOps environments Desirable: Legal sector experience (preferred) Professional services or regulated industry experience (FS, insurance, consulting, etc.) TOGAF or equivalent architecture framework Azure certifications Exposure ...

Senior Software Engineer Engagement : Full‐Time Contractor Location : London / Hybrid Length: 12 month contract Role Summary We are seeking a software engineer specialising in distributed data systems to design and build low‐latency, high‐volume data processing solutions that underpin regulatory voice compliance assurance across the Bank … Define and implement scalable data models using Hive and Hadoop ecosystems Apply software engineering best practices : version control, code reviews, testing, CI / CD and documentation Reverse‐engineer and modernise legacy batch or reporting‐oriented implementations Implement data quality, integrity, lineage and auditability controls required ...

DevOps Engineer £550 / day Inside IR-35 for an initial 6 months SC - possibility to to fresh clearances if yours has recently lapsed Reading / Leeds - predominantly remote We're looking for a DevOps Engineer to design, build and operate reliable CI / CD ...

projects – designing and implementing robust, scalable solutions Collaborate with senior management to ensure infrastructure aligns with business goals Maintain and improve CI / CD pipelines and monitoring systems Drive best practices across infrastructure and cloud operations Provide technical expertise to ensure system reliability, security … have top academics and would like to apply, we would love to hear from you. Please ensure when applying you include your degree classification / GPA or equivalent on your resume. Please send an up-to-date resume via the relevant link. We’re committed to creating an inclusive ...

full development lifecycle. You will provide technical leadership for one of our clients' development squads, driving secure, scalable & maintainable solutions for both backend and / or frontend technologies. Key skills required: Excellent track record in a similar role (Tech Lead, Lead Developer, Senior Architect) C#, .NET Core Cloud experience … Azure) React, TypeScript, Next.js CI / CD, Docker Microservices Agile Experience leading and mentoring junior team members Happy working with other teams The role is paying up to £90,000 + benefits and will be hybrid working with 3 days per week in the Liverpool ...

closely with Data Engineering to improve platform scalability, governance, observability, and performance across a GCP-native stack. Hands-On Delivery Contribute directly to SQL / dbt development, model reviews, architecture decisions, and analytics workflows where needed. Improve Data Quality Establish testing, lineage, monitoring, and documentation standards to improve trust … Strong hands-on experience with: BigQuery dbt SQL Looker GCP-native analytics environments Strong understanding of: Data modelling ELT workflows Metric governance Data quality / testing frameworks Self-serve analytics principles Experience partnering with Product, Commercial, or Operational stakeholders in fast-moving environments. Comfortable balancing strategic leadership with hands ...

business intelligence (BI) systems. Re-engineering manual data flows to enable scaling and repeatable use. Supporting the build of data streaming systems. Writing ETL / ELT scripts and code to make sure the process performs optimally. Developing data models to support self-service business intelligence reporting that … recognised qualification. Previous experience in a similar role. Knowledge of Azure ETL services (Data Factory, Synapse etc). Experience of using CI / CD, MS Azure and Azure Dev Ops in an agile environment. Knowledge and understanding Strong proficiency in T-SQL and writing quality ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and" appropriate use "of data." Define advanced experimental designs, lead A / B testing, develop and" maintain "metrics and dashboards," establish "robust" MLOps "practices, and own"end-to-end" productionisation "from data ingestion through deployment and ongoing … extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML / DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and" appropriate use "of data." Define advanced experimental designs, lead A / B testing, develop and" maintain "metrics and dashboards," establish "robust" MLOps "practices, and own"end-to-end" productionisation "from data ingestion through deployment and ongoing … extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML / DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and" appropriate use "of data." Define advanced experimental designs, lead A / B testing, develop and" maintain "metrics and dashboards," establish "robust" MLOps "practices, and own"end-to-end" productionisation "from data ingestion through deployment and ongoing … extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML / DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and" appropriate use "of data." Define advanced experimental designs, lead A / B testing, develop and" maintain "metrics and dashboards," establish "robust" MLOps "practices, and own"end-to-end" productionisation "from data ingestion through deployment and ongoing … extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML / DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and" appropriate use "of data." Define advanced experimental designs, lead A / B testing, develop and" maintain "metrics and dashboards," establish "robust" MLOps "practices, and own"end-to-end" productionisation "from data ingestion through deployment and ongoing … extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML / DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and" appropriate use "of data." Define advanced experimental designs, lead A / B testing, develop and" maintain "metrics and dashboards," establish "robust" MLOps "practices, and own"end-to-end" productionisation "from data ingestion through deployment and ongoing … extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML / DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and" appropriate use "of data." Define advanced experimental designs, lead A / B testing, develop and" maintain "metrics and dashboards," establish "robust" MLOps "practices, and own"end-to-end" productionisation "from data ingestion through deployment and ongoing … extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML / DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and" appropriate use "of data." Define advanced experimental designs, lead A / B testing, develop and" maintain "metrics and dashboards," establish "robust" MLOps "practices, and own"end-to-end" productionisation "from data ingestion through deployment and ongoing … extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML / DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI / ...