Artificial Intelligence/Machine Learning Engineer

About the role

You will oversee the full lifecycle of applied artificial intelligence solutions in support of federal clients. The role requires you to translate complex mission requirements into robust machine learning pipelines and data-driven decision frameworks. You will operate at the intersection of software engineering and data science to deliver scalable, secure, and verifiable systems. This position is integral to maintaining the performance and reliability of deployed AI capabilities in regulated environments. You will collaborate with technical and mission partners to ensure alignment with strategic objectives and compliance mandates. The work demands meticulous attention to validation standards and a disciplined approach to model lifecycle management. You will be accountable for delivering solutions that balance advanced analytical methods with operational constraints and security protocols.

Key facts

What you'll do

• Assume responsibility for end to end development and deployment of machine learning applications in alignment with federal requirements.
• Conduct comprehensive requirements analysis to define data needs, performance metrics, and acceptance criteria for AI initiatives.
• Select appropriate data sets and preprocess raw information to ensure suitability for modeling and compliance with governance standards.
• Perform statistical analysis to characterize data distributions, validate assumptions, and derive actionable insights that inform model development.
• Run machine learning algorithms across diverse scenarios to evaluate accuracy, robustness, and generalizability under realistic conditions.
• Use results to improve models through iterative experimentation, hyperparameter tuning, and feature engineering guided by empirical evidence.
• Design or select appropriate data and knowledge representation methods that facilitate efficient storage, retrieval, and interpretation of information.
• Recognize software architecture, data modelling, and data structures to ensure that implemented solutions integrate cleanly within existing technical ecosystems.
• Provide system integration oversight to coordinate model deployment, monitor operational behavior, and manage interfaces with downstream applications.
• Oversee test and evaluation of AI and ML algorithms through an iterative design process to meet verification and validation requirements.
• Research and implement a broad range of AI and ML algorithms and tools, selecting approaches that best address the problem domain and regulatory context.
• Run standard test and evaluation protocols to quantify model performance, document outcomes, and support evidence based decision making.
• Train and retrain systems when needed to maintain relevance, adapt to evolving data patterns, and sustain high levels of predictive fidelity.
• Experience in working with various ML libraries and packages to leverage established tools and accelerate development cycles.

Requirements

• You need United States Citizenship as mandated by federal contract requirements, accompanied by the ability to obtain and maintain position appropriate security clearance, such as Active TS/SCI security clearance with agency appropriate polygraph.
• You need to demonstrate capabilities in designing, developing, and maintaining machine learning solutions that adhere to stringent operational and compliance standards.
• You need to select and apply appropriate data sets while ensuring that data sourcing, handling, and usage comply with established policies and regulatory frameworks.
• You need to perform statistical analysis using rigorous methods to assess data quality, identify biases, and validate analytical assumptions.
• You need to run machine learning algorithms and evaluate their behavior across diverse conditions to confirm that objectives and performance thresholds are met.
• You need to provide system integration oversight to ensure that machine learning components interoperate effectively within broader technical architectures.
• You need to oversee test and evaluation of AI and ML algorithms through an iterative design process, documenting procedures, results, and deviations to satisfy verification and validation requirements.
• You need experience in working with various ML libraries and packages, showing familiarity with tools commonly employed in applied research and production grade implementations.
• You need to run standard test and evaluation protocols, recording metrics, observations, and conclusions in a clear, reproducible manner.
• You need to train and retrain systems when required, adapting models to new data, updated requirements, or changes in the operational environment.
• You need to design or select appropriate data and knowledge representation methods that support efficient processing, accurate interpretation, and long term maintainability.
• You need to recognize software architecture, data modelling, and data structures to anticipate integration challenges and guide the selection of appropriate technical approaches.

Nice to have

No additional preferred qualifications or desirable attributes are specified in the source material.

Practical notes

Note: Due to federal contract requirements, United States Citizenship and position appropriate security clearance is required. (e.g. Active TS/SCI security clearance with agency appropriate polygraph).

Wyetech, LLC is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

For , Affirmative Action Statement: Wyetech, LLC is committed to the principles of affirmative action in all hiring and employment for minorities, women, individuals with disabilities, and protected veterans.

For , Accommodations: If you require reasonable accommodation to access or complete the application process due to a disability, you may contact the Wyetech, LLC human resources team for assistance.

For , Capabilities: Candidates must possess the demonstrated ability to work independently and collaboratively in a federally funded environment, manage multiple priorities, and maintain strict adherence to documentation and procedural requirements.

For , Select appropriate data sets: You will be responsible for evaluating data sources, assessing data quality, and determining the suitability of data sets for specific analytical and operational objectives.

For , Perform statistical analysis: You will apply statistical methods to explore data, test hypotheses, and validate assumptions, ensuring that analytical results are reliable and interpretable.

For , Run machine learning algorithms: You will execute machine learning workflows, including training, validation, and testing, while monitoring algorithm behavior and performance metrics.

For , Use results to improve models: You will analyze experiment outcomes, diagnose issues such as overfitting or data leakage, and implement refinements to enhance model effectiveness.

For , Train and retrain systems when needed: You will establish schedules and criteria for model retraining, ensuring that deployed systems remain accurate and responsive over time.

For , Experience in working with various ML libraries and packages: You will leverage common frameworks and libraries to implement solutions efficiently and in alignment with community best practices.

For , Run standard test and evaluation protocols: You will follow defined procedures for assessing model performance, recording results, and reporting findings to stakeholders.

For , Provide system integration oversight: You will coordinate with software engineers and infrastructure teams to ensure that machine learning components are deployed and maintained effectively.

Oversee test and evaluation of AI and ML algorithms through an iterative design process to meet verification and validation requirements. This includes planning evaluation activities, defining test conditions, executing assessments, capturing observations, and documenting conclusions to demonstrate compliance with established standards and contractual obligations.