Data Engineer

Become an AI data engineer in a team which will play a critical role in infusing Red Hat products with generative AI. In this role, you will collaborate with data scientists and software engineers to build and maintain high-leverage data sets containing Red Hat's unique experience and expertise, to be used for fine-tuning large language models and creating RAG databases of high quality. Your data sets will influence and will be influenced by Red Hat infrastructure built from ground up to support the fine-tuning process. You will not only build the data sets. You will also participate in design, deployment, configuration and optimization of the infrastructure around the data. The ideal candidate will therefore be excited about the data, the science and the code.

You will contribute directly to Red Hat's rapidly growing AI/ML (artificial intelligence and machine learning) family of products. This is a very high profile project and the position is critical to the project's future success. It includes a lot of flexibility and therefore requires a highly motivated and self-driven individual.

Primary Job Responsibilities

• Design systems, integrations and processes required to achieve the best fine tuning results, including selection and integration of data sources, data pre-processing and subsequent quality evaluation.
• Design, build, and maintain scalable data pipelines for extracting, transforming, and loading (ETL) data from internal Red Hat systems into LLM training process
• Develop and optimize databases to ensure efficient data storage and retrieval.
• Design and develop data warehousing solution to support large scale data storage.
• Utilize Python for data manipulation, automation, and analysis. Ensure high quality data is used as an input for model fine tuning and RAG building.
• Contribute to the entire stack, from active participation in the fine tuning process to the implementation of and ongoing optimization of the designed systems
• Collaborate with other team members (data scientists, software engineers) as well as other teams to deliver a best-in-class solution and maintain it.
• Work in a fast-paced agile globally distributed environment of talented engineers

Required Skills

• Bachelor's degree in Computer Science, Data Science, or a related field
• 2-4 years of work experience in data engineering, preferably in AI/ML contexts
• Extensive, advanced experience with Python development.
• Strong understanding of LLM architectures, training processes, and data requirements
• Experience with RAG systems, knowledge base construction, and vector databases
• Familiarity with embedding techniques, similarity search algorithms, and information retrieval concepts
• Hands-on experience with data cleaning, tagging, and annotation processes (both manual and automated)
• Strong self-motivation, problem solving and organizational skills.
• Collaborative attitude and willingness to share ideas openly.
• Excellent English written and verbal communication skills.
• Ability to quickly learn and use new tools and technologies

Preferred skills

• Experience with AI and Machine Learning platforms, tools, and frameworks, such as: Tensorflow, PyTorch, LLaMA.cpp, and Kubeflow.
• Familiarity with different LLM parameters like temperate, top-k, and repeat penalty, and different LLM outcome evaluation data science metrics and methodologies.
• Experience with various vector store technologies and their applications in AI
• Experience with Cloud Native Technologies and Platforms (e.g. Kubernetes)
• Understanding of data lakehouse concepts and architectures
• Experience with agile development, CI/CD systems and DevOps methodology
• Experience with big data storage techniques, such as Parquet, Avro, and S3.