Description
Seize your opportunity to make a personal impact as an Artificial Intelligence and Machine Learning Engineer. GDIT is your place to make meaningful contributions to challenging projects and grow a rewarding career.
At GDIT, people are our differentiator. As a Machine Learning Engineer, you will help ensure today is safe and tomorrow is smarter.
HOW A MACHINE LEARNING ENGINEER WILL MAKE AN IMPACT
- Develop and adapt Large Language Models (LLM) and Natural Language Processing (NLP) methodologies using artificial intelligence and machine learning (AI/ML) frameworks and programming languages to create new capabilities to improve analytic workflows and address key intelligence questions.
WHAT YOU’LL NEED TO SUCCEED:
- Education: Bachelor or Master’s Degree in an IT discipline or the equivalent combination of education, technical certifications or training, or work experience
- Experience: 8+ years
- Technical skills:
- Professional or academic experience working with modern deep learning frameworks such as PyTorch, TensorFlow, or Keras.
- Hands-on experience using GPUs for accelerated computing.
- Professional or academic experience in testing, evaluating, or validating the performance of AI systems (with a focus on LLM-based systems).
- Professional or academic experience in experiment design and execution to test the performance of LLMs against a benchmark.
- Experience tuning neural networks (including LLMs) on custom datasets and applying them to specific use cases.
- Experience building AI/ML models and ensembles, selecting appropriate Python libraries, preparing data, performing analyses, and evaluating model performance.
- Proficiency in Python or R
- Solid SQL skills, including working with to include using common table expressions, set operations, aggregated functions and nested subqueries.
- Experience using version control tools such as GitHub and Jenkins.
- Security Clearance Level: TS/SCI with Polygraph
- Location: McLean, VA, On Customer Site
Skills and abilities desired:
- Experience working with Hugging Face Transformers and its model hub.
- Demonstrated professional or academic experience in the development of benchmarks to measure LLM performance.
- Experience with cloud-based development and architecture.
- Experience with front-end or application frameworks like Flask.
- Ability to build text-focused machine learning solutions (classification, topic modeling) using SciKit-Learn or deep-learning approaches.
- Experience developing applications for semantic search.
- Proficiency creating dashboards and visualizations in Tableau.
- Ability to communicate modeling decisions, methodologies, and results clearly to technical and non-technical audiences.
- Experience building or using verification and validation test benches.
- Familiarity with Explainable AI (XAI) techniques.
- Experience working with ONNX (Open Neural Network Exchange).
Benefits:
- 401K with company match
- Comprehensive health and wellness packages
- Internal mobility team dedicated to helping you own your career
- Professional growth opportunities including paid education and certifications
- Cutting-edge technology you can learn from
- Rest and recharge with paid vacation and holidays