AI Explainability Engineer Intern

We're looking for an AI Explainability Engineer Intern to join our Leidos team!

The candidate helps to ensure that our AI systems are not both effective and interpretable. You will work with data scientists, machine learning engineers, and other stakeholders to develop AI tools. Your work assists in making the AI understandable to a large group of audiences. The candidate designs and implements explainability techniques by researching new methods and collaborating with cross-functional teams to integrate AI. The role requires an understanding of AI and machine learning principles and excellent problem-solving and communication skills. The AI solutions will be deployed on low-size, weight, and power endpoints. Therefore, the candidate must be familiar with maximizing capabilities when resources are limited.

Along with those skills, the candidate must have demonstrated the ability to work independently and in technical teams to implement and customize algorithms to fuse multiple data modalities. In this position at Leidos Arlington, VA. the candidate should have at least intermediate Python coder ability and hands-on experience using ML libraries like SciKit Learn, DKube, KubeFlow, Feast, Azure, TensorFlow, Keras, etc. The candidates' knowledge should also include experience containerizing AI models and using the containers with AWS, Microsoft Azure, or Google Cloud.

Primary Responsibilities

• Experiment with and test different explainability models for efficiency and understanding.
• Implement explainability models into AI solutions.
• Understand capabilities like SHAP and LIME.
• Familiarity with options for edge computing.
• Solve complex problems with multilayered data sets, and optimize existing machine learning libraries and frameworks 
• Collaborate with data scientists, administrators, data analysts, data engineers, and data architects on production systems and applications   
• Identify differences in data distribution that could potentially affect model performance in real-world applications
• Ensure algorithms generate accurate user recommendations
• Stay up to date with developments in the machine learning industry
• Develop, deploy, and manage AI/ML models, including Generative AI models (GPT, DALL-E, etc.), to solve business problems.
• Work with data scientists to integrate AI/ML models into production environments.
• Fine-tune models, manage version control and monitor performance in production systems.
• Develop and maintain CI/CD pipelines to automate model deployment and web application releases.
•  Implement DevOps best practices for infrastructure as code (IaC) using tools like Docker, Kubernetes, and Terraform.
• Conduct anomaly detection using various AI/ML techniques
• Engineer prompts for LLMs and Generative AI
• Use algorithms to identify complex patterns across multiple modalities
• Increase the efficiency and quality of data alignment and fusion
• Enhance and maintain analysis tools, including automation of current processes using AI/ML algorithms quantitative data analysis, including developing retrieval, processing, fusion, analysis, and visualization of various datasets
• Configure and program prototypes Jupyter notebooks with ML solutions
• Setup and use AWS instances to train and operate AI/ML models

Basic Qualifications
College students actively seeking a B.S. degree in Aerospace Engineering, Computer Science, Mathematics, Statistics, Physics, Electrical Engineering, Computer Engineering, or related fields

• Must be able to obtain a Top-Secret security clearance with a polygraph security clearance
• US citizenship required
• Knowledge of Deep Learning Frameworks such as Keras, Tensorflow, PyTorch, Mxnet, etc. - Ability to apply these frameworks to real problems in the 'time --series' domain
• Assist in the development and testing of commercial web applications
• Collaborate with senior developers on various software development projects
• Apply user-centered design principles in web application development
• Participate in agile development processes and team meetings
• Contribute to the improvement of existing software and the creation of new features
• Intermediate software development skills lifecycle including developing and maintaining good production quality code
• Hands-on Software Development Skills (Python-Preferred)
• Experience or educational courses/projects in Machine Learning and Text

Preferred Qualifications

• Visualizations/Web Development Skills (e.g., Tableau, D3).
• Hands-on experience with prototype development
• Hands-on experience with automating data cleansing, formatting, staging, and transforming data human
• Hands-on experience applying data analytics
• Hands-on experience with prompt engineering
• Hands-on experience with reinforcement learning
• Hands-on experience with LLMs and Generative AI
• Hands-on experience with intelligent systems and machine learning
• Experience with the interpretability of deep learning models
• Big Data Skills (Azure, Hadoop, Spark, recent deep learning platforms)
• Experience with text mining tools and techniques, including in areas of summarization, search (e.g., ELK Stack), entity extraction, training set generation (e.g., Snorkel), and anomaly detection
• Hands-on experience with DKube
• Hands-on experience with KubeFlow
• Hands-on experience with Feast

Original Posting Date:

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:

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.