ARTIFICIAL INTELLIGENCE ENGINEER JOB DESCRIPTION

An Artificial Intelligence Engineer in this field builds systems that must earn a sponsor's sign-off before they ever reach a warfighter or analyst. The work sits inside defense and national security programs, where eligibility for a US government security clearance is a baseline condition of employment, not a preference. These engineers evaluate AI solutions against sponsor requirements rather than market demand, and many efforts only progress if they can transition from a research prototype into an operational system. That transition, more than any single algorithm, is what separates this role from a typical commercial AI engineering job.

As the Artificial Intelligence Engineer, you design and implement machine learning and AI algorithms aimed at national security and defense challenges, working inside multi-modal sensor, decision-support, or autonomy-focused programs. You collaborate with domain experts, sponsors, and technical staff to move solutions from prototype toward operational use.

Career Impact: Holding or qualifying for a US government security clearance differentiates your candidacy across the broader defense AI contractor base.

Business Impact: Sponsor evaluation of your AI solutions directly determines whether a program advances from research toward fielded operational use.

Growth Opportunity: Engineers who lead trade studies and architecture evaluations on these programs typically progress toward Lead or principal engineering roles overseeing sponsor relationships.

• Design machine learning algorithms for multi-modal sensor and decision-support applications.
• Develop AI software using modern software engineering techniques and practices.
• Evaluate AI solutions against sponsor requirements and operational needs.
• Collaborate with domain experts and engineers to resolve critical technical challenges.
• Support trade studies, proof-of-concept activities, and architecture evaluations.
• Translate algorithms and technical specifications into fielded production code.
• Mentor junior engineers on technical approach and sponsor deliverables.
• Maintain awareness of advances in AI capability across industry and academia.

• Bachelor's degree in computer science, engineering, or a related technical field, or equivalent experience.
• 3 or more years of applied machine learning or AI engineering experience, with production deployment exposure.
• Experience building and deploying deep learning models in a production environment.
• Working proficiency in Python, with experience in C++ or Java.
• Ability to contribute to engineering trade studies and architecture evaluations.
• Excellent written and verbal communication skills for technical and sponsor audiences.
• Eligibility to obtain and maintain a US government security clearance.

• Active DoD Secret or higher security clearance already in place.
• Advanced degree in computer science, AI, or a related discipline.
• Experience supporting defense or aerospace technology platform development.
• Experience with autonomy, decision-support, or human behavior modeling systems.

• Sponsor acceptance rate of delivered AI solutions against stated requirements.
• Number of prototypes transitioned from research into operational or fielded use.
• Cycle time from algorithm design to integrated test session readiness.
• Defect rate identified during integrated test sessions with sponsors and partners.
• Clearance-eligible headcount retained on program, reflecting sponsor staffing continuity.

• Base Salary Range: $95,000 to $145,000 depending on clearance level and experience
• Bonus: Typically 5 to 10 percent of base, program-dependent
• Equity: Rare outside small defense AI firms; occasionally offered
• Health Benefits: Medical, dental, and vision coverage, employer-subsidized
• PTO: 15 to 20 days annually plus federal holidays
• Common Perks: Clearance sponsorship, relocation assistance, tuition support

Figures are estimates based on general US market benchmarks and may be outdated. Adjust based on location, company size, and seniority level.

Employment with this organization requires the ability to obtain and maintain a US government security clearance, which generally requires US citizenship and a background check free of disqualifying convictions. All qualified applicants will be considered without regard to race, color, religion, sex, national origin, age, disability, or any other status protected under applicable federal, state, and local law. Reasonable accommodations are available upon request for the application process. Final offers remain contingent on successful completion of required background screening and verification of work authorization in the United States.

The Artificial Intelligence Engineer owns the design and deployment of machine learning algorithms applied to complex multi-modal sensor data, working alongside domain experts and machine learning engineers. Reporting into the broader technical program, this work supports stakeholders in applying sound AI/ML solutions to operational requirements while expanding the team's technical portfolio.

Key Responsibilities

• Investigate machine learning, artificial intelligence, and statistical techniques applied to complex multi-modal sensor data.
• Design and implement machine learning algorithms and deploy solutions into production.
• Develop machine learning software using modern software engineering techniques.
• Maintain knowledge of the latest advances in AI capabilities across industry and academia.
• Collaborate with domain experts and other machine learning engineers to address critical technical challenges.
• Engage with stakeholders to analyze operational requirements and apply sound AI/ML technology solutions.
• Identify additional project opportunities to expand the technical work portfolio.
• Support rapid lab prototyping, field testing, technical benchmarking, and modeling and simulation for AI/ML applications.

Required Qualifications

• Bachelor of Science in Artificial Intelligence or a related technical field.
• Bachelor's degree, 3 years with a Master's degree, or a PhD with immediately applicable experience, or an equivalent combination of education and work experience.
• Experience developing data pre-processing pipelines, constructing customized deep learning models, and deploying models in a production environment.
• Experience in one or more deep learning domains, including object detection, image segmentation, facial recognition, or anomaly detection.
• Experience with one or more deep learning development frameworks, including TensorFlow, PyTorch, or Keras.
• Ability to lead or contribute to engineering trade studies, proof-of-concept activities, performance analyses, and architecture design and evaluation.
• Excellent written and verbal communication and presentation skills, with the ability to clearly explain machine learning solutions to a technical audience.
• Keen interest in learning the state of the art in the field and rapidly responding to new problems across a variety of domains.
• Eligibility for a government security clearance is required.

Embedded within MITRE's Intelligent Enterprise strategy, the Artificial Intelligence Engineer implements performant AI systems based on open-source and commercial solutions while troubleshooting issues related to data, access, and security permissions. Working closely with technical developers, operational support staff, and leadership, this work drives adoption of enterprise search and AI solutions across the organization.

Key Deliverables

• Implement performant AI systems based on open-source and commercial solutions.
• Troubleshoot technical issues related to AI systems, including challenges with data, access, and security permissions.
• Analyze performance data and formulate insights.
• Translate them into actionable next steps.
• Lead functional testing of search and AI solutions.
• Communicate with leadership to influence change and with end users to ensure adoption of enterprise search and AI solutions.

Education & Experience

• Bachelor's degree in Computer Science, Computer Engineering, or an AI-related field of study, or equivalent work experience.
• Minimum of 5 years of related experience with a Bachelor's degree, 3 years with a Master's degree, or a PhD with immediately applicable experience, or an equivalent combination of education and work experience.
• 2+ years of experience with artificial intelligence, machine learning, deep learning, data engineering, natural language processing, and machine learning.
• Hands-on experience with AI/ML platforms, including Microsoft Azure, Amazon SageMaker, or Elastic.
• Hands-on experience with tools including Python, TensorFlow, and AWS.
• Proven ability to learn new technologies, techniques, processes, languages, platforms, and systems independently.
• Strong analytical capabilities with a propensity for accuracy and attention to detail.
• Excellent communication skills, including the ability to explain difficult concepts using simple language and graphics.

Reporting to senior technical leadership, the Lead Artificial Intelligence Engineer develops and implements AI algorithms to address critical national and global challenges, evaluating solutions against sponsor requirements. Partnering with staff across one or more projects, this role provides mentorship and technical guidance that supports the transition of research results to operations.

Primary Duties

• Develop and implement AI algorithms to address critical national and global challenges.
• Develop AI-related software using modern software engineering techniques.
• Maintain knowledge of advances in AI capabilities across industry and academia.
• Evaluate AI solutions against sponsor requirements and needs.
• Contribute to the technical work program of one or more projects.
• Provide technical guidance focused on successful sponsor outcomes and transition of research results to operations.
• Provide leadership, mentorship, and collaborative technical advice to staff.

Skills & Qualifications

• Bachelor's degree in Computer Science, Engineering, Statistics, Applied Mathematics, Cybersecurity, or a related technical field.
• An advanced degree in a related field of study is preferred.
• 8+ years of work experience in machine learning, deep learning, computer vision, statistics, or related fields.
• Proven experience with statistical methods, neural networks, computer vision, machine learning, deep learning, algorithmic optimization, data science, and software engineering.
• Hands-on experience with tools including C/C++, Python, TensorFlow, Keras, PyTorch, dlib, and database languages.
• Outstanding written and oral presentation skills for both internal and external communications.

Sitting at the intersection of machine learning engineering and large-scale data infrastructure, the Artificial Intelligence Engineer designs and codes batch and real-time ML pipelines within a cross-functional team of engineers and scientists. Operating across geographically distributed teams, this work drives continuous improvement in an agile environment while delivering minimum viable products that bring the technical vision to life.

Core Functions

• Design and code large-scale batch and real-time ML pipelines in a cross-functional team of machine learning engineers and scientists.
• Prototype creative solutions by developing minimum viable products and implementing the technical vision.
• Communicate and collaborate with geographically distributed cross-functional teams.
• Participate in code reviews to assess overall code quality and flexibility.
• Resolve problems and roadblocks as they occur and help unblock junior team members.
• Drive continuous improvement within an agile development team.
• Participate in user story creation in collaboration with the team.
• Support and troubleshoot data and system issues as needed.

Requirements

• Bachelor's or Master's degree in software engineering, computer science, or a related technical field, or equivalent professional experience.
• 3+ years of experience in software development and machine learning engineering.
• Proficiency in Python and Scala or Java.
• Good understanding of machine learning pipelines and frameworks, including TensorFlow and PyTorch, with experience delivering real ML projects to a production environment.
• Experience building and maintaining APIs and streaming applications in a hybrid or cloud infrastructure.
• Strong command of big data technologies, including Hadoop, Hive, and Spark.
• Familiarity with cloud services such as AWS and workflow orchestration tools such as Airflow.
• Experience working with Agile/Scrum methodologies.

A key member of a cross-disciplinary team, the Artificial Intelligence Engineer develops AI solutions across medical, industrial, and consumer application fields, building proof-of-concept prototypes and breadboards from concept through validation. Collaborating across software, hardware, and customer teams, this work guarantees the specifications, architecture, and concept validation of AI systems at the system level.

Operational Focus

• Develop AI solutions for a wide range of application fields, including medical, industrial, and consumer applications.
• Develop concepts, make design decisions, and select the most optimal solution in collaboration with cross-disciplinary experts.
• Build proof-of-concept prototypes and breadboards.
• Guarantee the specifications, architecture, technical follow-up, and concept validation of AI systems.
• Support software and hardware developments from concept through to test and validation.
• Coordinate the integration of software and hardware at the system level.
• Communicate clearly and efficiently with project team members and customers.

Knowledge Skills & Abilities

• Master's degree in engineering, physics, or computer science, or equivalent experience.
• Formal or informal training in artificial intelligence or data science, including machine learning and related areas, or equivalent experience.
• Good grasp of AI and machine learning methodologies, machine learning toolboxes, building and deploying AI models, data preprocessing, and data analytics.
• Proficiency in Python.
• Thorough analytical insight with the ability to quickly understand technical problems and propose solutions.
• Broad technical interest with the ability to think in a multidisciplinary manner and a result-oriented approach.
• Fluency in English with strong communication skills.

Strong global game development depends on the Artificial Intelligence Engineer, who develops and improves AI systems for current and future titles using Unreal Engine and writes clean, well-documented C++ code. Based within a multidisciplinary studio team, this work contributes to engineering culture and workflow improvements while researching fresh ideas from across the games industry.

Day-to-Day Responsibilities

• Develop and improve AI systems for current and future titles using Unreal Engine.
• Write clean C++ code and maintain clear documentation for the team.
• Collaborate with a multidisciplinary team to develop unique solutions to complex engineering problems.
• Contribute to defining engineering culture and improving engineering workflows across the studio.
• Research games to bring fresh ideas.
• Implement and maintain game features.

Professional Experience

• Bachelor's degree in computer science, mathematics, physics, or engineering, or equivalent games industry experience.
• 3+ years of experience building highly immersive games or experiences.
• Experience with AI systems, academically or in shipped titles, with additional experience in animation or gameplay programming preferred.
• Development experience in C++ and working knowledge of Unreal Engine 4.
• Experience solving complex engineering problems, working with early-stage prototypes from concept through to launch.
• Highly skilled verbal and written communication across different disciplines within the studio.

As the Artificial Intelligence Engineer, this role develops AI-driven solutions that model human behavior and applies AI and machine learning techniques to complex tasks, including image analysis and reconstruction. The engineering team relies on this work to evaluate and improve application performance across artificial intelligence and machine learning domains, including problems within the petroleum engineering space.

Job Functions

• Develop AI-driven solutions that model human behavior to accomplish complex tasks or processes.
• Implement AI and machine learning solutions to solve a variety of complex problems.
• Analyze and associate AI principles with reasoning and uncertainty across varied environments.
• Apply AI and machine learning techniques for image analysis and reconstruction.
• Evaluate and improve the performance of applications in artificial intelligence and machine learning domains.

Background & Experience

• Bachelor's degree or higher in Computer Science, Mathematics, or a related technical field, or equivalent practical experience.
• Direct experience building machine learning solutions.
• Experience coding in one or more languages, including Python or C++, with experience in data structures, algorithms, and software design.
• Experience working with AI planners, PDDL, or automated planning.
• Experience developing REST microservices with TypeScript, Java, Python, or Golang.
• Knowledge of containerization technologies, including Docker and Kubernetes.
• Understanding of distributed applications and production ML systems.
• Understanding of petroleum engineering domain problems.

Artificial Intelligence Engineer develops and improves algorithms within a finite-state machine architecture, reviewing current algorithms and identifying missing steps in the process. Success in the position means structuring and analyzing quantitative data and translating complex market information into insights stakeholders can understand and act on.

Accountabilities

• Develop and improve algorithms within a finite-state machine architecture.
• Review all current algorithms.
• Identify missing steps in the process.
• Develop new steps in current algorithms.
• Analyze and structure quantitative data.

Position Requirements

• Degree in artificial intelligence or a related field.
• 3+ years of work experience in artificial intelligence or a related field.
• Knowledge of Python.
• Ability to structure and analyze quantitative data.
• Ability to translate complex market information into understandable insights for stakeholders.
• Pragmatic, solution-oriented approach with well-developed communication skills.

The Autonomy/Artificial Intelligence Engineer produces integrated software algorithms that structure, analyze, and leverage data across structured and unstructured environments, applying machine learning and deep learning techniques to areas including virtual reality, augmented reality, and robotics. Reporting through the advanced technology organization, this work supports the full technology lifecycle of new products and features, from conceptualization through release, while serving as an active interface to clients and the external technical community.

Strategic Responsibilities

• Plan, prepare, and present product introduction strategies.
• Provide consultation in the early life cycle of the product.
• Apply technical principles and theories to develop new concepts and contribute to development in the field.
• Develop and program integrated software algorithms to structure, analyze, and leverage data in structured and unstructured environments.
• Develop and communicate descriptive, diagnostic, predictive, and prescriptive insights and algorithms.
• Use machine learning and statistical modeling techniques to develop and evaluate algorithms that improve product performance, quality, and data accuracy.
• Translate algorithms and technical specifications into code using current programming languages and technologies.
• Apply deep learning technologies to visualize, learn from, and respond to complex situations.
• Adapt machine learning to areas including virtual reality, augmented reality, robotics, and other interactive products.
• Apply knowledge of experimental methodologies, statistics, optimization, and probability theory using both general-purpose and statistical software for tool building and modeling.

Minimum Qualifications

• Bachelor's degree in Computer Science, Mathematics, Statistics, Machine Learning, Engineering, or a related field, plus 5–7 years of experience.
• Solid foundation in computer science, autonomy, and artificial intelligence with strong object-oriented coding skills in C++ and Python.
• Experience with deep learning libraries, including TensorFlow, Keras, PyTorch, Theano, or Caffe.
• Experience with machine learning techniques, including support vector machines, neural networks, Markov decision processes, and natural language processing.
• Knowledge of data structures, numerical optimization, and algorithm complexity.
• Experience with software development, coding algorithms, and Agile methodology and repositories.
• Experience supporting national security space capabilities development is preferred.

The Artificial Intelligence Engineer builds AI and ML systems capable of making large-scale logistics decisions, developing, testing, and deploying systems that improve delivery speed, estimate precision, last-mile optimization, and emissions reduction. Reporting through a startup engineering organization, this work collaborates with stakeholders across product, engineering, data science, and external academic and AI/ML partners to advance e-commerce logistics outcomes.

Areas of Ownership

• Build an AI and ML system capable of making large-scale logistics decisions.
• Develop, test, and deploy systems to improve e-commerce logistics processes, including delivery speed, precision of delivery estimates, last-mile optimization, and emissions reduction.
• Use infrastructure-as-code and CI/CD tools to deploy models.
• Develop tools and APIs to integrate data models into applications.
• Collaborate with internal stakeholders across product, engineering, and data science, as well as external academic and AI/ML partners.

Technical Qualifications

• Degree in Computer Science, Software Engineering, Statistics, Mathematics, or a related field, or equivalent experience; an MSc or PhD is preferred.
• Professional software development experience on real-world commercial products.
• Experience in multiple programming languages, with proficiency in at least one; current stack includes Go, Node.js, and Python.
• Experience contributing to the architecture and design of new and existing systems, including design patterns, reliability, and scaling.
• In-depth understanding of machine learning and deep learning algorithms and at least one deep learning framework, including PyTorch or TensorFlow.
• Practical experience building AI/ML systems and addressing challenges such as overfitting, class imbalance, and bias replication.
• Experience using large datasets to build predictive models with a solid understanding of computer science fundamentals, including data structures and algorithm design.
• Experience applying machine learning and artificial intelligence in supply chain, logistics, or operations research is preferred.

Embedded within Tulco Labs' AI Factory model, the Artificial Intelligence Engineer develops and implements deep learning solutions for business problems across a portfolio of traditional industries undergoing digital transformation. Working closely with a team of engineers and researchers, this individual contributor writes proof-of-concept software and measures analytical impact from conception through communicating results to clients.

Areas of Ownership

• Develop and implement deep learning solutions for business problems.
• Develop insight from data using a variety of methodologies.
• Assist project teams with measuring impact, from conception of the analytical approach through to communicating results.
• Write software at the core of project proof-of-concepts.
• Collaborate with a team of engineers and researchers to address emerging client needs.
• Build products as an individual contributor.

Required Qualifications

• Bachelor's, Master's, or PhD in Computer Science, Data Science, or a related field.
• 5+ years of experience in a corporate setting with applied data science problems.
• Hands-on knowledge and experience with deep learning, including deep neural networks, recurrent networks, and convolutional networks, using at least one production framework such as TensorFlow, PyTorch, or Keras.
• Experience with a variety of training strategies, including cross-validation and holdout sets.
• Practical experience with unsupervised machine learning methods such as k-means or PCA; experience with unsupervised deep learning methods or GANs is a strong plus.
• Prior experience with statistical inference approaches and reinforcement learning is a plus.
• Excellent interpersonal, written, and oral communication skills with an entrepreneurial, self-directed work style.

Reporting to the engineering manager, the Artificial Intelligence Engineer develops applications that predict failures in network service validation based on historical failure data and defect correlation. Partnering with customers, users, and less experienced team members, this work supports application deployment in test and production environments while resolving production issues as they arise.

Activities

• Develop applications that predict failures in network service validation based on historical failure data and defect correlation.
• Lead and participate in collaborative brainstorming sessions with customers and users.
• Provide application design and documentation.
• Develop and execute unit test plans and integration test plans.
• Mentor less experienced team members.
• Support application deployment in test and production environments and resolve production issues.

Qualifications & Experience

• Experience with data ETL and data analysis packages and workflows.
• Experience with machine learning packages, including XGBoost, scikit-learn, and TensorFlow.
• Experience with end-to-end data analysis, including data wrangling via SQL or Python, statistical modeling, and hypothesis development.
• Proficiency in Python programming in a Unix environment.
• Knowledge of Git, JIRA, and Zephyr.
• Experience with SAFe/Agile development processes.
• Strong written and verbal communication skills.

Sitting at the intersection of machine vision and advanced control systems, the Artificial Intelligence Engineer translates conceptual algorithms into engineering requirements while scouting, assessing, and applying novel technologies in deep learning and data science. Operating in support of the manager's technology roadmap, this work develops proof-of-concept prototypes and ensures technology solutions follow industry best practices.

Engineering Responsibilities

• Translate conceptual algorithms into engineering requirements.
• Conceptualize breakthrough solutions involving machine vision, machine learning, and artificial intelligence.
• Scout, assess, and apply novel technologies related to machine vision, deep learning, machine learning, data science, and advanced control systems.
• Support the manager in creating, assessing, and managing technology roadmaps.
• Develop proof-of-concept prototypes and implement studies into products.
• Ensure technology solutions follow industry best practices.

Knowledge Skills & Abilities

• Master's degree in Electronic Engineering, Physics, or Mathematics.
• Relevant experience in the development of machine vision, machine learning, deep learning, and data science.
• Relevant experience in neural networks, control theory, and system modeling and simulation.
• Knowledge of systems engineering and basic project management, including Gantt and Agile methodologies.
• Excellent written and verbal communication skills
• Ability to articulate challenging technical concepts to both lay and expert audiences.