Senior Machine Learning Engineer (Knowledge Graph) in Capgemini Engineering

Purpose Of The JobWe are looking for an experienced Machine Learning engineer with experience in Large Language Model (LLM) application development. The client's focus is on delivering technology that evolves the practice of medicine and helps patients live longer, better lives. They are a diverse team of open and friendly people, enthusiastic about technological novelties and optimal enterprise solutions. They share knowledge, experience & appreciate different points of view. As a Senior ML engineer, you will work closely with multi-disciplinary teams to design, develop and deploy structured, high-quality data solutions in particular NLP solutions. These solutions will be leveraged across the organization to help fulfill our client's mission: to do now what patients need next.Main Tasks And ResponsibilitiesPartner with the Data Scientists and cross functional teams to solve complex problems and create unique solutions by using modern NLP technologies including LLMs.Build data pipelines and deployment pipelines for ML models.Use ML models in combination with Knowledge Graph or other Knowledge Solutions according to business and functional requirements.Able to help deploy various technology stacks and tune them for better performance.Document and communicate the design and implementation details.Contribute to the client's AI team on technical decisions.Collaborate with clients, informatics departments to deploy scalable and easy-to-maintain solutions.Serves as a technical point of contact for enterprise wide technologies solutions.Leads complex troubleshooting efforts and root cause analysis.Education, Skills And Experience MUST HAVE:Bachelor’s degree in Computer Science/Engineering or equivalent work experience in information technology environment (networking, infrastructure, database).3+ years of commercial Data Engineering / ML Engineering / MLOps / UI/UX engineering experience4+ years of commercial software engineering experienceExperience with LLM agents including tool using and reasoning, for instance, the combination of RAG solution and code interpreter.Experience with Knowledge Graph, Knowledge Base, SPARQL, Ontology and/or Semantic Web.Experience with LLM fine tuning a plusExperience in building data pipelines and deployment pipelines for LLM applicationsRecent experience with ML/AI toolkits such as AWS Sagemager (other toolkits like Pytorch, Tensorflow, Keras, MXNet, H20, etc are nice to have).Experience with MLOps technologies (Sagemaker, Vertex AI, Kubeflow)Experience with cloud solutions (AWS / Azure / GCP), dockerProven scripting and automation skillsGood knowledge of: git, bash, linux, CI/CD tools (e.g. jenkins, gitlab CI), software lifecycle, RDB, visualization tools eg Tableau, Jira, confluenceProgramming languages: Python, RTest driven development, good coding practicesProblem-solving and decision-making skills.Good interpersonal skills.Customer & delivery focus.Ability to work effectively with team members and virtual teams from different locations and different cultural backgrounds.Would Be a PlusExperience with deployment of scalable appsExperience with clinical study dataShow more Show less Position level Senior secondary level Type of employment Full-time Job responsibilities Engineering and Information Technologies Industries IT services and IT Consulting