LexisNexis Legal & Professional is a leading global provider of legal, regulatory and business information and analytics that help customers increase productivity, improve decision-making and outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis® ...
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We are looking for a skilled LLM Application Developer to join our team. You will be responsible for implementing large language model (LLM) based applications, working with proprietary and open-source models as well as popular frameworks such as LangChain or LlamaIndex to ensure seamless integration and deployment.
RESPONSIBILITIES
Manage a team of Machine Learning Engineers and Data Engineers
Collaborate with stakeholders like Product Managers, Data Scientists and Program Managers
Develop and implement LLM-based applications.
Fine-tune and deploy large language models.
Implement production quality ETL jobs
Build RAG-based applications
Integrate models with existing systems and APIs.
Preprocess and manage data for training and deployment.
Collaborate with cross-functional teams to define, design, and ship new features.
Write clean, maintainable, and efficient code.
Document development processes, code, and APIs.
REQUIREMENTS
Prior experience managing an engineering team
Proven experience with large language models and open-source frameworks.
Experience leveraging models from repositories such as Hugging Face
Experience with deep learning frameworks such as PyTorch, Tensorflow and Hugging Face Transformers.
Strong knowledge of API integration (RESTful, GraphQL).
Experience with data preprocessing, SQL, and NoSQL databases as well as vector stores (e.g., Postgres, Elasticsearch/OpenSearch, ChromaDB etc.)
Experience with GPU programming, including CUDA or RAPIDs
Familiarity with deployment tools (Docker, Kubernetes).
Excellent problem-solving and communication skills.
Ability to work collaboratively in an agile team environment.
PREFERRED QUALIFICATIONS
Degree in Computer Science, Data Science, or related field.
Certifications in machine learning, data science, or cloud computing.
Portfolio showcasing past projects or contributions to open-source projects.
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