Siemens Healthineers is Looking for Prompt Engineer at Bengaluru Full Time

Prompt Engineer

About Us

The Center
for Competence (CoC) team on Generative AI within Siemens Healthineers Development
center is responsible for providing productivity gains for the Product
development lifecycle for the R&D organizations with a services, solutions
and tool development to be used in the development of internal and external
applications.

Job description:

The primary role is to harness the power of prompt-based AI
models, such as GPT (Generative Pre-trained Transformer) models, to generate
human-like text or responses to specific queries or tasks. These models have a
wide range of applications, including natural language understanding, chatbots,
content generation, and more. A Prompt Engineer is responsible for configuring
and fine-tuning these models to produce desired outputs efficiently and
effectively.

Roles and Responsibilities:

Model Configuration : Configure the AI model with
appropriate prompts and parameters to achieve desired text generation outcomes.
This involves understanding the specific use case and tailoring the model
accordingly.

Fine-tuning: Fine-tune pre-trained models on specific
datasets to adapt them to the intended task or domain. This process requires
expertise in transfer learning and data preprocessing.

Prompt Engineering: Craft effective prompts that
elicit the desired responses from the AI model. This may involve designing
templates, specifying context, and optimizing prompt input.

Performance Optimization : Continuously optimize the
model’s performance in terms of output quality, coherence, and relevance.
Implement techniques like temperature scaling, top-k sampling, and nucleus
sampling to control the output.

Data Management : Handle data related to prompts and
model inputs effectively. Ensure data integrity, cleanliness, and appropriate
encoding for input into the AI model.

Monitoring and Debugging: Monitor model behavior and
performance, identify issues, and debug problems as they arise. This includes
addressing issues related to biased or inappropriate outputs.

Scaling and Deployment: Deploy prompt-based AI models
in production environments, ensuring they can handle a high volume of requests
efficiently and reliably. Implement model versioning and monitoring.

Ethical Considerations: Be aware of ethical
considerations, such as bias, fairness, and privacy, and take steps to mitigate
potential issues in the generated text.

Documentation: Maintain documentation of prompt configurations,
model versions, and best practices for prompt engineering. Share knowledge
within the team.

Collaboration : Collaborate with cross-functional
teams, including data scientists, machine learning engineers, and domain
experts, to align the model’s behavior with project objectives.

Key Skills Required:

Natural Language Processing (NLP): Proficiency in NLP
concepts and techniques, including tokenization, text generation, and language
modeling.

Deep Learning: Understanding of deep learning fundamentals,
especially transformer-based models like GPT.

Programming Languages: Strong programming skills,
particularly in Python, for scripting and model implementation.

Model Fine-tuning: Experience with fine-tuning pre-trained
language models and transfer learning techniques.

Prompt Design: Ability to design effective prompts that
produce desired AI model responses.

Data Handling: Skills in data preprocessing, data
management, and data encoding for AI model inputs.

Performance Optimization: Knowledge of techniques to
optimize the quality and diversity of generated text.

Deployment: Experience in deploying AI models in production
environments using cloud services or containerization.

Ethical AI: Awareness of ethical considerations in AI,
especially in text generation, and strategies to address biases and fairness
issues.

Collaboration and Communication: Strong teamwork and
communication skills to work effectively with multidisciplinary teams and
stakeholders.

Monitoring and Debugging: Proficiency in monitoring model
behavior and debugging issues in real-time.

Documentation: Ability to maintain clear and organized
documentation for prompt configurations and model performance.

A skilled Prompt Engineer plays a crucial role in harnessing
the capabilities of prompt-based AI models to deliver contextually relevant and
high-quality text generation solutions across various domains and applications.