Artificial Intelligence/Machine Learning Engineer, Junior

Summary

EverWatch is a government solutions company providing advanced defense and intelligence support. They are seeking a Junior Artificial Intelligence/Machine Learning Engineer to develop and deploy AI/ML solutions that enhance operational workflows and improve data accessibility for critical national security missions.

Responsibilities

• Cyber and intelligence analysts rely on multi-step workflows that are time-sensitive, detail-rich, and critical to national security
• As an AI/ML Engineer at EverWatch Solutions, you will work directly with mission users to develop and deploy artificial intelligence and machine learning solutions that enhance operational workflows, improve data accessibility, and support rapid decision-making in secure environments
• You will collaborate with operators, analysts, software developers, and mission leadership to capture operational needs and translate them into effective AI-enabled capabilities
• Your work may include developing LLM-powered workflows, agent-based automation, and other AI/ML solutions that streamline analytical tasks and improve mission effectiveness
• You will support the integration of AI capabilities into existing operational systems while ensuring solutions are reliable, scalable, and compliant with security and governance requirements in classified environments
• Additionally, you will contribute to data pipeline development, model evaluation, workflow optimization, and operational testing to support production-ready AI solutions

Skills

• 1-4 years of experience with Python for data analysis and machine learning tasks through academic, internship, or project-based work
• Knowledge of machine learning concepts including supervised learning, model evaluation, and data preprocessing
• Familiarity with standard data science libraries and development tools
• Ability to think analytically, solve problems effectively, and learn quickly in a fast-paced, mission-oriented environment
• Ability to collaborate within a team and communicate technical concepts clearly
• TS/SCI clearance with a polygraph
• Bachelor's degree in computer science, Data Science, Electrical Engineering, Mathematics, Statistics, or a related technical field or master's degree with limited experience
• Experience with academic coursework, thesis work, or capstone projects involving machine learning, natural language processing, or data science applications
• Experience with version control tools such as Git and collaborative development environments
• Knowledge of deep learning frameworks such as PyTorch or TensorFlow
• Knowledge of large language models (LLMs) and generative AI concepts
• Knowledge of cloud platforms such as AWS, Azure, or GCP
• Knowledge of containerization technologies such as Docker or Kubernetes
• Knowledge of agentic AI, retrieval-augmented generation (RAG), or other applied NLP techniques
• Prior internship, co-op, research, or project experience supporting government, defense, or intelligence community environments

Qualifications

Must Haves

• 1-4 years of experience with Python for data analysis and machine learning tasks through academic, internship, or project-based work
• Knowledge of machine learning concepts including supervised learning, model evaluation, and data preprocessing
• Familiarity with standard data science libraries and development tools
• Ability to think analytically, solve problems effectively, and learn quickly in a fast-paced, mission-oriented environment
• Ability to collaborate within a team and communicate technical concepts clearly
• TS/SCI clearance with a polygraph
• Bachelor's degree in computer science, Data Science, Electrical Engineering, Mathematics, Statistics, or a related technical field or master's degree with limited experience

Nice to Haves

• Experience with academic coursework, thesis work, or capstone projects involving machine learning, natural language processing, or data science applications
• Experience with version control tools such as Git and collaborative development environments
• Knowledge of deep learning frameworks such as PyTorch or TensorFlow
• Knowledge of large language models (LLMs) and generative AI concepts
• Knowledge of cloud platforms such as AWS, Azure, or GCP
• Knowledge of containerization technologies such as Docker or Kubernetes
• Knowledge of agentic AI, retrieval-augmented generation (RAG), or other applied NLP techniques
• Prior internship, co-op, research, or project experience supporting government, defense, or intelligence community environments