STINGRAI Cognitive Science (AI/ML) Engineer (Engineer Machine Learning 2) - 29202

HII's Mission Technologies division•Washington, DC

4d•$99,000 - $175,000•Onsite

About The Position

This opportunity resides with All-Domain Operations (ADO), a business group within HII’s Mission Technologies division. All-Domain Operations comprises multi-domain operations, platforms and logistics, and intelligence operations. HII designs, develops, integrates and manages the sensors, systems and other assets necessary to support integrated ISR operations and accelerated decision-making. With data fusion and mission management capabilities for the Department of Defense, the combatant commands and the intelligence community, HII advances the mission around the globe. Leadership at HII is a mindset, not a title. Through our Leadership Capability Framework, we define how every employee grows, leads, and contributes—regardless of role. It sets the standard for how you can develop yourself and what you can expect from leaders across our organization. We look for candidates who want to grow in alignment with these capabilities: Know & Grow Your People – Commit to learning and supporting team success. Build Relationships – Communicate openly, collaborate well, and build trust. Take Ownership – Deliver on commitments and take pride in your work. Customer First – Focus on the mission and those we serve. Shape the Future – Bring ideas, curiosity, and continuous improvement. Act with Urgency – Take initiative and follow through with purpose. These capabilities guide how all employees contribute to our shared success across Mission Technologies. HII – Mission Technologies is seeking a Cognitive Science (AI/ML) Engineer. The Cognitive Science Engineer supports innovative research, advanced technology development, and the integration of emerging AI and machine‑learning capabilities across mission‑focused programs. This role applies deep expertise in artificial intelligence, machine learning, data science, and software engineering to develop new algorithms, assess cutting‑edge technologies, and provide strategic insights to senior decision‑makers. The engineer evaluates the feasibility and defense applicability of new technological concepts, creates data‑mining architectures, develops analytical models, and designs advanced AI solutions tailored to large and complex datasets. This position also contributes to modeling and simulation environments, integrates AI engines into enterprise systems, and conducts research into advanced ML techniques—including those used for Radio Frequency (RF) data processing. This requisition supports hiring at multiple experience levels. Final placement will be determined based on the selected applicant’s qualifications, experience, and skill sets. STINGRAI: Advancing Mission Success Through Intelligence, Innovation, and Operational Excellence Every day, HII helps U.S. Southern Command (SOUTHCOM) and its mission partners stay ahead of evolving threats by delivering the intelligence, technology, and operational expertise needed to protect U.S. interests across the Western Hemisphere. Join our team on STINGRAI and support mission-critical operations through advanced intelligence, surveillance, cyber, engineering, and all-domain capabilities that strengthen regional security, enable informed decision-making, and help defend our nation today while preparing for tomorrow's challenges.

Requirements

Demonstrated experience researching, designing, developing, and implementing AI/ML algorithms and models
Strong understanding of data‑mining methodologies, statistical analysis, and large‑scale data processing
Experience developing analytical architectures, data models, and protocols that support trend identification and decision advantage
Experience with deep learning, neural networks, and advanced ML frameworks
Proficiency with supporting technologies, including cloud platforms, containerization tools, parallel computing, databases, and Git
Experience integrating AI/ML capabilities with modeling, simulation, or advanced analytic environments
Strong understanding of software‑development lifecycles, DevOps practices, algorithm verification, and system integration
Demonstrated ability to communicate complex technical concepts to both technical and non‑technical stakeholders
Proven ability to self‑manage workload, prioritize tasks, and deliver high‑quality results in a dynamic environment
Must possess and maintain a Top-Secret clearance

Nice To Haves

Knowledge of RF data processing or experience applying ML to signal‑processing problem sets

Responsibilities

Support innovative research efforts by leveraging advanced AI/ML expertise to evaluate, develop, and transition emerging technologies
Provide strategic assessments of current and emerging technologies, delivering insights to senior leaders on feasibility, risk, and defense applications
Conduct background research to evaluate novel technological concepts and their relevance to mission needs
Develop data‑mining architectures, models, protocols, statistical reporting, and analytic methodologies to identify trends in large and complex datasets
Research, design, and develop advanced AI algorithms and solutions at the intersection of AI and data science
Apply AI and ML methods to refine, optimize, and enhance existing and newly developed algorithms
Provide analysis, requirements development, algorithm design, implementation, integration, verification, and maintenance for AI software systems
Collaborate across multi‑functional teams to identify opportunities for improving enterprise‑level IT services and advanced engineering solutions
Research and implement ML techniques tailored for processing Radio Frequency (RF) data
Exercise a strong understanding of software systems, deep learning, AI design methods, and system‑of‑systems architectures
Leverage supporting technologies such as cloud computing, containerization, parallelization, database systems, and Git‑based source management
Participate in algorithm design, targeting techniques, classification frameworks, and ML development cycles
Integrate AI engines and ML techniques into modeling and simulation applications
Follow standard DevOps practices, including source control, change management, and release planning
Manage workload independently and ensure timely completion of tasks and deliverables