Junior Machine Learning Engineer

Integration Innovation, Inc. (i3) • Hopewell, VA

6d • Onsite

About The Position

i3 is hiring a Junior Machine Learning Engineer to support development of Department of Defense systems. The engineer will develop and program neural-network-based software solutions and assist in analyzing AI-enabled systems. The position is located in Arlington, Virginia.

The role involves prototyping and implementing machine-learning software under the guidance of senior engineers and ML architects; researching and evaluating neural-network architectures; developing, testing, and debugging Python and C++ software; preparing datasets and training and evaluation pipelines; optimizing models; and conducting reproducible experiments with technical documentation of implementations, methods, and results.

Candidates must have a relevant bachelor’s degree, 0–2 years of relevant experience, familiarity with neural-network architectures for classification, Python programming experience, familiarity with C/C++, and working knowledge of an ML framework such as PyTorch. Applicants must be U.S. citizens and able to obtain a SECRET security clearance. A master’s degree and experience with model training, ML performance profiling, GPU acceleration, hardware description languages, technical documentation, or reverse engineering are preferred.

Requirements

• Bachelor’s degree in electrical engineering, computer engineering, computer science, mathematics, or a related field.
• 0–2 years of relevant experience, including internships, academic research, or project work.
• Familiarity with neural-network architectures and their application to classification problems.
• Programming experience in Python and familiarity with C/C++.
• Working knowledge of at least one machine-learning framework, such as PyTorch.
• Foundational understanding of linear algebra, probability, and optimization.
• Strong analytical and problem-solving skills and the ability to learn new tools and technologies.
• Ability to obtain a SECRET security clearance.
• U.S. citizenship required.

Nice To Haves

• Master’s degree in electrical engineering, computer engineering, computer science, or mathematics.
• Experience training, evaluating, or fine-tuning neural-network models.
• Familiarity with profiling machine-learning workloads and identifying performance bottlenecks.
• Exposure to GPU computing, CUDA, tensor cores, or other machine-learning acceleration technologies.
• Familiarity with hardware description languages such as VHDL or Verilog.
• Experience writing technical documentation for software, research, or engineering projects.
• Experience reverse engineering software, hardware designs, or compiled code to understand system behavior and identify underlying functionality.

Responsibilities

• Prototype and implement software-based machine-learning systems under the guidance of senior engineers and ML architects.
• Research and evaluate neural-network architectures for specific problems and application requirements.
• Develop, test, and debug Python and C++ software for a neural-network-based software suite.
• Curate and generate datasets, develop training and evaluation pipelines, and optimize models for accuracy and performance.
• Conduct reproducible experiments and create technical documentation describing implementations, methodologies, and results.
• Assist in the analysis of AI-enabled systems.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level