GenAI Developer Intern

Description

As a GenAI Developer Intern at Leidos, you will have the opportunity to work on cutting-edge projects that combine machine learning, Large Language Models (LLMs), and prompt engineering to drive innovation. You'll be assisting in design, development, and deployment of complex solutions in distributed and cloud environments, working with large datasets and text-based data to create innovative technical solutions.

What You'll Gain:

• Hands-on experience with machine learning models, web APIs, and cloud deployments
• Opportunity to work with large volumes of data and develop innovative solutions
• Experience with LLMs and prompt engineering techniques
• Collaboration with experienced professionals in the field
• Development of strong scripting skills in Python
• Exposure to a fast-paced and dynamic work environment
• Opportunity to work on cutting-edge projects and contribute to the development of AI technologies

Primary Responsibilities:

• Work with Large Language Models (LLMs) to develop and fine-tune models for specific tasks
• Design and optimize prompts for LLMs to achieve desired outcomes
• Experiment with different prompt engineering techniques to improve model performance
• Design and develop machine learning models using Python programming language

• Deploy solutions in distributed and cloud environments
• Analyze and optimize existing machine learning models and big-data applications
• Perform text analytics, log analysis, and issue resolution
• Collaborate with cross-functional teams to guide business decisions
• Develop strong scripting skills in Python using Linux/Windows environments

Basic Qualifications:

• Currently pursuing a degree in Computer Science, AI, or related field
• Strong foundation in machine learning, deep learning, and programming languages (Python) and using iPython notebooks
• Basic understanding of LLMs and prompt engineering concepts.
• Familiarity with popular LLM frameworks and libraries (e.g. Hugging Face Transformers)
• Experience in one or more areas of machine learning / artificial intelligence such as classifications, NLP, Anomaly Detection, Sentiment Analysis, and Clustering
• Experience in using deep learning frameworks such as TensorFlow, NLTK, PyTorch or Keras, etc.
• Experience in solving NLP problems such as text categorization, text clustering/topic modeling, entity extraction, text summarization, etc.
• Experience in developing and managing pipelines using Databricks, manage user workspaces, notebooks, clusters.
• Proficient in traditional databases (MS-SQL) with T-SQL, including writing optimized SQL queries.
• Excellent communication skills to communicate with wide technical and business users
• Demonstrate ability to build full stack systems architected for speed and distributed computing.
• Demonstrate ability to quickly learn new tools and paradigms to deploy cutting edge solutions
• Adept at simultaneously working on multiple projects, meeting deadlines, and managing expectations
• Ability to obtain and maintain a Public Trust clearance - US citizenship or permanent residency required.

Preferred Qualifications:

• Experience with prompt engineering techniques such as few-shot learning, zero-shot learning, and chain-of-thought prompting.
• Knowledge of LLM architectures such as transformer-based models and recurrent neural networks
• Experience or understanding in as AWS Bedrock, AWS SageMaker, Azure Machine Learning Studio, or similar ML/DS platform.
• Familiarity with GenAI and experience applying Large Language Models (LLMs) to unstructured data.
• Good exposure to cloud technologies such as AWS S3, Lambda functions, or Azure Data lake etc.,
• Familiarity with version control systems, specifically Git, and experience with platforms like Azure DevOps.
• Knowledge of parallel computing approaches such as use of GPU parallelization is highly desirable
• Develop both deployment architecture and scripts for automated system deployment in AWS or on-premise systems.
• Proficient in Linux and AWS CLI, with hands-on experience in using these tools.

While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

The Leidos pay range for this job level is a general guideline onlyand not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

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