About the job

Do you like the energy of a brand new team where you have the opportunity to influence your future way of working? Do you think broadly about the importance of both software and data engineering in your projects?  Are you attracted to the idea of a virtual assistant which is more than just a wrapper on top of somebody else’s large language model technology? We are building a team to develop and deliver Red Hat’s own flavor of Large Language Model (LLM) to power our product-supporting virtual assistants, and we are looking for people like you.

Become an AI software engineer with a data engineer focus, in a team which will play a critical role in infusing Red Hat products with generative AI. In this combined role, you will have two focus areas:

Collaborate with other software engineers to design and develop our generative AI platform; and

Collaborate with data scientists 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’ll not only build the data sets - You will also participate in design, deployment, configuration and optimization of the project’s code and infrastructure. 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.

What you will do

Participation in architectural designs, technology choices as well as setting and meeting a high bar for quality that will impact adoption by a very diverse group of internal customers.

Participation in developing features, fixing bugs, mitigating security threads, reviewing code and writing automated tests for the project

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 solutions 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

What you will bring

Bachelor's degree in computer science, or equivalent related work experience.

Experience in data engineering, preferably in AI/ML contexts.

Experience with Python software development.

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

The following is considered a plus

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.

Understanding of LLM architectures, training processes, and data requirements

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.

About Red Hat

Red Hat is the world’s leading provider of enterprise open source software solutions, using a community-powered approach to deliver high-performing Linux, cloud, container, and Kubernetes technologies. Spread across 40+ countries, our associates work flexibly across work environments, from in-office, to office-flex, to fully remote, depending on the requirements of their role. Red Hatters are encouraged to bring their best ideas, no matter their title or tenure. We're a leader in open source because of our open and inclusive environment. We hire creative, passionate people ready to contribute their ideas, help solve complex problems, and make an impact.

Inclusion at Red Hat
Red Hat’s culture is built on the open source principles of transparency, collaboration, and inclusion, where the best ideas can come from anywhere and anyone. When this is realized, it empowers people from different backgrounds, perspectives, and experiences to come together to share ideas, challenge the status quo, and drive innovation. Our aspiration is that everyone experiences this culture with equal opportunity and access, and that all voices are not only heard but also celebrated. We hope you will join our celebration, and we welcome and encourage applicants from all the beautiful dimensions that compose our global village.

Equal Opportunity Policy (EEO)
Red Hat is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.

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