AI Developer Intern

Together, we can beat cancer.

At Varian, a Siemens Healthineers Company, we bring together the world's best talent to realize our vision of a world without fear of cancer. Together, we work passionately to develop and deliver easy-to-use, efficient oncology solutions.

We are part of an incredible community of scientists, clinicians, developers, researchers, professionals, and skilled specialists pushing the boundaries of what’s possible, to improve people’s lives around the world. We embrace a culture of inclusivity in which the power and potential of every individual can be unleashed. We spark ideas that lead to positive impact and continued success.

If you want to be part of this important mission, we want to hear from you.

This is an exciting opportunity for an aspiring AI Developer to join our dynamic Data team, focusing on the cutting-edge field of Large Language Models (LLM). In this role, you'll be at the forefront of analyzing and interpreting vast datasets to inform support the development and optimization of state-of-the-art LLMs. Collaborating closely with our data scientists and engineers, you will contribute to leveraginge big data to improve and innovate LLM capabilities, enhancing their understanding and generation of human-like text. Your work will be instrumental in driving our data-centric AI strategies forward, utilizing advanced analytics to uncover insights that will shape the future of our LLM projects. You will be a pivotal member of our team, helping to transform complex data into actionable intelligence that fuels AI innovation and elevates our solutions to new heights of performance and efficiency.

Are you in between studies or looking for an internship - this is your chance to gain work experience in an international environment!

As an AI Developer Intern, your responsibilities will include:

Model Development and Training: Participate in the development and training of large language models, including preprocessing data, selecting appropriate neural network architectures, and optimizing model parameters.

Research and Implementation: Conduct research on the latest LLM techniques and best practices. Implement experimental models based on cutting-edge research to explore new capabilities or improve existing model performance.

Data Analysis and Preprocessing: Work with large datasets to clean, preprocess, and ensure the data is suitable for training LLMs. This may involve text normalization, tokenization, and dealing with missing or corrupted data.

Model Evaluation: Evaluate the performance of language models using appropriate metrics. Analyze model behavior and identify areas for improvement, such as reducing bias or increasing accuracy in specific tasks.

Collaboration: Collaborate with developers, and cross-functional teams to contribute to the development of LLM projects. Participate in code reviews, documentation, and sharing findings with the team.

Technical Documentation: Document the development process, including the design choices, methodologies adopted, and the rationale behind them. Prepare reports and presentations to communicate findings and progress to both technical and non-technical audiences.

Qualifications

Educational Background: Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

Programming Skills: Proficiency in programming languages such as Python, and familiarity with libraries and frameworks relevant to AI and ML (e.g., TensorFlow, PyTorch, Keras).

Understanding of Machine Learning and NLP: Solid understanding of machine learning algorithms, deep learning architectures (e.g., Transformers), and natural language processing techniques.

Mathematical and Statistical Knowledge: Strong foundation in mathematics and statistics, particularly in areas relevant to AI and ML like linear algebra, probability, and calculus.

Research Skills: Ability to conduct research, synthesize information from academic papers, and apply theoretical knowledge to practical model development.

Problem-Solving Skills: Strong analytical and problem-solving skills, with the ability to work on complex problems and propose innovative solutions.

Communication Skills: Excellent written and verbal communication skills to effectively document and present work.

Collaborative Attitude: Willingness to work in a team, learn from feedback, and contribute positively to a collaborative environment.

This is an exciting opportunity for an aspiring AI Developer to join our dynamic Data team, focusing on the cutting-edge field of Large Language Models (LLM). In this role, you'll be at the forefront of analyzing and interpreting vast datasets to inform support the development and optimization of state-of-the-art LLMs. Collaborating closely with our data scientists and engineers, you will contribute to leveraginge big data to improve and innovate LLM capabilities, enhancing their understanding and generation of human-like text. Your work will be instrumental in driving our data-centric AI strategies forward, utilizing advanced analytics to uncover insights that will shape the future of our LLM projects. You will be a pivotal member of our team, helping to transform complex data into actionable intelligence that fuels AI innovation and elevates our solutions to new heights of performance and efficiency.

Are you in between studies or looking for an internship - this is your chance to gain work experience in an international environment!

As an AI Developer Intern, your responsibilities will include:

Model Development and Training: Participate in the development and training of large language models, including preprocessing data, selecting appropriate neural network architectures, and optimizing model parameters.

Research and Implementation: Conduct research on the latest LLM techniques and best practices. Implement experimental models based on cutting-edge research to explore new capabilities or improve existing model performance.

Data Analysis and Preprocessing: Work with large datasets to clean, preprocess, and ensure the data is suitable for training LLMs. This may involve text normalization, tokenization, and dealing with missing or corrupted data.

Model Evaluation: Evaluate the performance of language models using appropriate metrics. Analyze model behavior and identify areas for improvement, such as reducing bias or increasing accuracy in specific tasks.

Collaboration: Collaborate with developers, and cross-functional teams to contribute to the development of LLM projects. Participate in code reviews, documentation, and sharing findings with the team.

Technical Documentation: Document the development process, including the design choices, methodologies adopted, and the rationale behind them. Prepare reports and presentations to communicate findings and progress to both technical and non-technical audiences.

Qualifications

Educational Background: Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

Programming Skills: Proficiency in programming languages such as Python, and familiarity with libraries and frameworks relevant to AI and ML (e.g., TensorFlow, PyTorch, Keras).

Understanding of Machine Learning and NLP: Solid understanding of machine learning algorithms, deep learning architectures (e.g., Transformers), and natural language processing techniques.

Mathematical and Statistical Knowledge: Strong foundation in mathematics and statistics, particularly in areas relevant to AI and ML like linear algebra, probability, and calculus.

Research Skills: Ability to conduct research, synthesize information from academic papers, and apply theoretical knowledge to practical model development.

Problem-Solving Skills: Strong analytical and problem-solving skills, with the ability to work on complex problems and propose innovative solutions.

Communication Skills: Excellent written and verbal communication skills to effectively document and present work.

Collaborative Attitude: Willingness to work in a team, learn from feedback, and contribute positively to a collaborative environment.

Varian is required to comply with all local and applicable regulations that may be associated with vaccine requirements for certain roles.

Fighting cancer calls for big ideas.

We envision a world without fear of cancer. Achieving this vision takes dedication and commitment from all of us, every single day. That's why we celebrate and value the distinctly beautiful and intersectional identities of each of our employees. We are a mirror of our patient-base, which allows us to innovate. Big ideas come from everywhere, and the best ideas are fostered by our unique individual experiences. At Varian, we encourage you to bring your whole self to work and believe your bold and authentic perspective will help to power more victories over cancer.

#TogetherWeFight

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