Parexel
Machine Learning Engineer-FSP
Parexel, Durham, North Carolina, United States, 27703
We are looking for an experienced Machine Learning engineer with experience in Large Language Model (LLM) application development to join The Product Development Digital Strategy & Enablement team (PD-DSE). In the DSE we focus on delivering technology that evolves the practice of medicine and helps patients live longer, better lives. We are a diverse team of open and friendly people, enthusiastic about technological novelties and optimal enterprise solutions. We share knowledge, experience & appreciate different points of view.
Your missionAs 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 PD organization to help our teams fulfill our mission: to do now what patients need next.
Job Responsibilities
Partner 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 DSE AI team on technical decisions.Collaborate with clients and informatics departments to deploy scalable and easy-to-maintain solutions.Serve as a technical point of contact for enterprise-wide technology solutions. Lead complex troubleshooting efforts and root cause analysis.
Your Qualifications And Experience
Experience 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 is a plus.Experience in building data pipelines and deployment pipelines for LLM applications.Recent experience with ML/AI toolkits such as AWS Sagemaker (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), Docker.Proven scripting and automation skills.Good knowledge of: git, bash, Linux, CI/CD tools (e.g. Jenkins, GitLab CI), software lifecycle, RDB, visualization tools e.g. Tableau, Jira, Confluence.Programming languages: Python, R.Test-driven development, good coding practices.Problem-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.Experience with deployment of scalable apps is a plus.Experience with clinical study data is a plus.
Education / Years Of Experience
Bachelor’s degree in Computer Science/Engineering or equivalent work experience in an information technology environment (networking, infrastructure, database).2+ years of commercial Data Engineering / ML Engineering / MLOps / UI/UX engineering experience.3+ years of commercial software engineering experience.
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Your missionAs 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 PD organization to help our teams fulfill our mission: to do now what patients need next.
Job Responsibilities
Partner 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 DSE AI team on technical decisions.Collaborate with clients and informatics departments to deploy scalable and easy-to-maintain solutions.Serve as a technical point of contact for enterprise-wide technology solutions. Lead complex troubleshooting efforts and root cause analysis.
Your Qualifications And Experience
Experience 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 is a plus.Experience in building data pipelines and deployment pipelines for LLM applications.Recent experience with ML/AI toolkits such as AWS Sagemaker (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), Docker.Proven scripting and automation skills.Good knowledge of: git, bash, Linux, CI/CD tools (e.g. Jenkins, GitLab CI), software lifecycle, RDB, visualization tools e.g. Tableau, Jira, Confluence.Programming languages: Python, R.Test-driven development, good coding practices.Problem-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.Experience with deployment of scalable apps is a plus.Experience with clinical study data is a plus.
Education / Years Of Experience
Bachelor’s degree in Computer Science/Engineering or equivalent work experience in an information technology environment (networking, infrastructure, database).2+ years of commercial Data Engineering / ML Engineering / MLOps / UI/UX engineering experience.3+ years of commercial software engineering experience.
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