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At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.
Our team consists of 100+ engineers, designers, data scientists, implementation, and product people, working in small inter-disciplinary teams closely with creative agencies, media agencies, and with our customers, to develop and scale our leading digital advertising optimization suite that delivers amazing outcomes for brands and audiences.
Our platforms are built with Python, React, and Clojure, are deployed using CI/CD, heavily exploit automation, and run on AWS, GCP, k8s, Snowflake, BigQuery, and more. We serve 9 petabytes and 77 billion objects annually, optimize thousands of campaigns to maximise ROI, and deliver 20 billion ad impressions across the globe. You’ll play a leading role in significantly scaling this further.
As our first Machine Learning Operations (MLOps) Engineer, you will play a pivotal role in bridging the gap between platform engineering, data science, and software engineering, building systems that drive the deployment, monitoring, and scalability of machine learning models. You will design and implement pipelines, automate workflows, and optimise model performance in training and production environments. You’ll lead the creation of process, implementation of tools, and creation of solutions mature how we integrate machine learning solutions into our production systems, while maintaining reliability, security, and efficiency. You’ll additionally play a leading role in driving continuous improvement in model lifecycle management, from development to deployment and monitoring.
Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 360,000 team members globally in more than 50 countries. With its strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms.
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At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.
Our team consists of 100+ engineers, designers, data scientists, implementation, and product people, working in small inter-disciplinary teams closely with creative agencies, media agencies, and with our customers, to develop and scale our leading digital advertising optimization suite that delivers amazing outcomes for brands and audiences.
Our platforms are built with Python, React, and Clojure, are deployed using CI/CD, heavily exploit automation, and run on AWS, GCP, k8s, Snowflake, BigQuery, and more. We serve 9 petabytes and 77 billion objects annually, optimize thousands of campaigns to maximise ROI, and deliver 20 billion ad impressions across the globe. You’ll play a leading role in significantly scaling this further.
As our first Machine Learning Operations (MLOps) Engineer, you will play a pivotal role in bridging the gap between platform engineering, data science, and software engineering, building systems that drive the deployment, monitoring, and scalability of machine learning models. You will design and implement pipelines, automate workflows, and optimise model performance in training and production environments. You’ll lead the creation of process, implementation of tools, and creation of solutions mature how we integrate machine learning solutions into our production systems, while maintaining reliability, security, and efficiency. You’ll additionally play a leading role in driving continuous improvement in model lifecycle management, from development to deployment and monitoring.
Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 360,000 team members globally in more than 50 countries. With its strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms.
,[Participate in the process and technology transformation projects within Finance, supporting Transformation Consultants and Transformation Managers in successful development of agreed project deliverables for internal as well as for external Clients, Participate in the projects that may be related but not limited to: target operating model design, process design, process and technology maturity assessment, benchmarking, GBS / SSC set up, automation potential assessment, ERP/Platform solutions implementation, RPA implementation, transition, training delivery, change management and similar, Learn and apply in practice different process improvement methodologies (e.g. Lean Six Sigma / DGEM Benchmarking / ESOAR / 5 senses of Intelligent Automation) to the area of expertise for the continuous improvement and transformation purposes, Prepare and own certain project deliverables related to documentation of identified process challenges, potential improvements and benefits, business requirement documents, solution documents, technical designs, benchmarking report out, Support data gathering as well as various analyses that will lead towards identification of improvement recommendations for clients, Learn the consulting techniques related to problem solving, design thinking, selling, and delivery of convincing presentation of your ideas, Keep abreast of technology technological developments, their strengths and weaknesses and suggest technology related improvements within the given area of expertise Requirements: SAP ECC, Oracle, Conducting workshops Additionally: Training budget, Sport subscription, Private healthcare, International projects, Free coffee, Bike parking, Free parking, Mobile phone, In-house trainings, Modern office, No dress code.