Candidate MUST:

Be currently located in the United States for the current three consecutive years.

Be US Citizen or US Person (Green Card Holder) with the ability to obtain a Public Trust Clearance.

Role is primarily telecommute (US ONLY)

Responsibilities:

- Stay up to date on the most current developments in the generative AI space.

-Deploy machine learning models and services on cloud platforms such as AWS, Google Cloud, or Azure. - Collaborate with cross-functional teams, including data scientists, researchers, and other engineers, to integrate LLMs and RAG into broader projects.

- Manage large datasets, including data cleaning, preprocessing, and transformation.

- Develop and maintain data pipelines to ensure seamless data flow for model training and evaluation.

- Communicate technical concepts and project progress to non-technical stakeholders and team members.

- Conduct experiments to fine-tune parameters and optimize model performance. - Implement techniques to improve the efficiency and scalability of LLM and RAG systems.

- Stay up-to-date with the latest advancements in NLP, machine learning, and deep learning fields to inform project strategies.

- Monitor and maintain deployed models to ensure they perform reliably and meet performance benchmarks.

- Ensure code quality by following best practices in software development, including version control, testing, and continuous integration/continuous deployment (CI/CD).

- Document code and maintain comprehensive technical documentation to support team knowledge sharing and project handovers.

Basic Qualifications

• Active Public Trust Clearance or Ability to obtain a Public Trust Clearance
• Bachelor's Degree and - 10+ years of experience delivering production ready , industrial strength code, and implementing CI/CD pipelines.
• - Proficiency in Python and familiarity with libraries such as TensorFlow and PyTorch. Extensive experience with neural network architectures, particularly transformers, and NLP techniques. RAG and Data Engineering:
• - Understanding of Retrieval-Augmented Generation (RAG) and hands-on experience with implementing RAG solutions.
• - Proficiency in handling and preprocessing large datasets, as well as experience with data pipelining and ETL processes.
• - Experience with cloud platforms like AWS, Google Cloud, or Azure for deploying ML models. Strong software engineering fundamentals, including version control, testing, and CI/CD.
• - Ability to design efficient algorithms for data retrieval and model training, and optimize models through hyperparameter tuning.

Additional Technical Skills

• - Experience with Large Language Models (LLM) and Retrieval-Augmented Generation (RAG) architecture
• Hands-on experience with the following:
• - Python, pytorch, tensofflow, pandas, Scikit-learn, teras and other AI/Ml libraries
• - JavaScript
• - Other object-oriented programming languages
• - React.js
• - Cloud Architecture Frameworks such as AWS well architected

hhsnih

Original Posting Date:

2025-01-22
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.

Pay Range:

Pay Range $104,650.00 - $189,175.00

The Leidos pay range for this job level is a general guideline only and 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.

#Remote