Junior Machine Learning Engineer

Integration Innovation • Arlington, VA

5d • Onsite

About The Position

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

The engineer will prototype and implement machine learning systems under the guidance of senior engineers and ML architects, research neural network architectures for specific applications, and develop, test, and debug software. The role also involves dataset preparation, training and evaluation pipelines, model optimization, reproducible experimentation, and technical documentation.

Applicants must be U.S. citizens and able to obtain a SECRET security clearance. The listed pay range is $93,000–$210,000; the posting notes that this range is a general guideline and not a guarantee of compensation.

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, familiarity with C/C++, and 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, with the ability to learn new tools and technologies.
• U.S. citizenship.
• Ability to obtain a SECRET security clearance.

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 with 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 produce 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