Senior AI/ML Developer/Engineer

Position summary

IGC is seeking a Senior AI/ML Developer/Engineer to design, build, deploy, and sustain machine-learning models and AI-enabled applications for a prospective federal artificial intelligence engineering program supporting a federal customer. You will move models from concept to production across approved enterprise cloud and technology platforms and collaborate closely with data scientists, software engineers, security personnel, and product teams.
This is a hands-on senior engineering role requiring strong applied machine-learning skills, disciplined engineering practices, and the ability to deliver reliable, secure, accessible, and maintainable solutions in a structured, collaborative government-contractor environment.

Key responsibilities

• Design and develop machine-learning models, algorithms, and AI-enabled applications.
• Implement, integrate, optimize, deploy, and sustain AI and machine-learning solutions.
• Work with data scientists, software engineers, cloud engineers, security personnel, and product teams to move models into production.
• Analyze large and complex datasets and produce actionable insights.
• Conduct data preprocessing, feature engineering, statistical analysis, model selection, training, testing, validation, and evaluation.
• Tune and improve model performance, reliability, accuracy, scalability, and maintainability.
• Evaluate emerging developments in AI and machine learning and recommend appropriate customer-approved uses.
• Maintain strong knowledge of machine-learning algorithms, design patterns, evaluation methods, and engineering principles.
• Create and maintain complete documentation for AI and machine-learning models, datasets, experiments, configurations, assumptions, evaluation results, performance metrics, limitations, decisions, and operating procedures.
• Work with deep-learning frameworks.
• Develop using Python and, where applicable, R, JavaScript, or other approved languages.
• Use Terraform or comparable customer-approved infrastructure-as-code practices.
• Develop and manage CI/CD pipelines and Git-based source-code management.
• Integrate logging, monitoring, tracing, metrics, alerting, and other observability capabilities into AI engineering efforts.
• Develop or integrate generative-AI, large-language-model, RAG, chatbot, document-processing, predictive-modeling, anomaly-detection, forecasting, or workflow-automation solutions.
• Develop AI-enabled interfaces and outputs that meet applicable Section 508 accessibility requirements, and participate in accessibility validation during applicable development iterations and releases.
• Support model monitoring, model-drift detection, responsible-AI controls, testing, security, privacy, access control, and production operations.
• Support onboarding or refactoring of existing AI applications into approved enterprise environments.
• Contribute to technical standards, reusable patterns, architecture documentation, operating procedures, test plans, and user guidance.
• Participate in Agile planning, reviews, demonstrations, retrospectives, and production-support activities.

Required qualifications

• Minimum of five years of relevant professional experience in AI engineering, machine learning, data science, or production software engineering.
• Demonstrated expertise in current artificial intelligence and machine-learning technologies, emerging techniques, model-development practices, and production AI engineering.
• Demonstrated experience designing and developing machine-learning models and algorithms.
• Experience implementing and optimizing AI or ML solutions and integrating models into production systems.
• Experience analyzing large and complex datasets.
• Experience developing, evaluating, tuning, and improving model performance and accuracy.
• Strong knowledge of machine-learning algorithms and principles.
• Experience documenting models, experiments, processes, and performance metrics.
• Familiarity with one or more deep-learning frameworks.
• Strong proficiency in Python, R, JavaScript, or another programming language used for production artificial intelligence and machine-learning development. Python proficiency is strongly preferred.
• Experience with Terraform or comparable infrastructure-as-code technology.
• Experience implementing or managing CI/CD pipelines.
• Experience with Git-based code management, branching, pull requests, reviews, and release controls.
• Experience integrating observability tools into AI or ML systems.
• Hands-on experience developing or integrating front-end, back-end, and full-stack application components used to operationalize AI and machine-learning solutions.
• Knowledge of HTML and CSS and front-end development practices supporting UI and UX, including front-end JavaScript and libraries such as React.
• Prototyping experience and visual communication skills.
• Knowledge of Section 508 accessibility requirements and accessible technology delivery.
• Testing and debugging experience, including familiarity with development tools used to evaluate application performance, usability, and page speed.
• Experience with DevOps, cloud computing, infrastructure, web development, and software architecture.
• Ability to work within Agile development and delivery environments and to collaborate with product owners, technical teams, security personnel, data specialists, and federal stakeholders rather than in isolation.
• Bachelor’s or master’s degree in computer science, artificial intelligence, machine learning, software engineering, data science, or a closely related technical field.

Preferred qualifications

• Ten or more years of relevant experience.
• Master’s degree in a relevant technical field.
• Experience with Azure AI services, Azure Machine Learning, Azure OpenAI, Azure AI Foundry, AWS SageMaker, GCP Vertex AI, or comparable approved cloud AI platforms.
• Experience developing RAG solutions, chatbots, document intelligence, translation, summarization, predictive analytics, fraud or anomaly detection, or optimization models.
• Experience with MLOps, model registries, experiment tracking, model monitoring, responsible AI, prompt evaluation, or LLM evaluation.
• Experience with FedRAMP-authorized cloud or SaaS environments.
• Federal security, privacy, ATO, CUI, Section 508, or NIST experience.
• Relevant Azure, AWS, GCP, machine-learning, data-science, security, or DevOps certifications.

Security and employment conditions

• U.S. citizenship is required.
• Ability to obtain and maintain a favorably adjudicated federal public-trust suitability determination before entry on duty, unless the customer formally grants temporary eligibility under its applicable procedures.
• Ability to complete and maintain all required federal training, including security awareness, privacy, unauthorized-disclosure training, controlled unclassified information (CUI), sensitive information and For Official Use Only (FOUO) safeguarding, rules of behavior, operational security (OPSEC), insider threat, and nondisclosure requirements.
• Ability to comply with applicable federal security, privacy, access-control, acceptable-use, and information-protection requirements.

Work location and schedule

• This role is primarily remote, with occasional attendance at customer sites in the Washington, DC and Northern Virginia region when required.
• Standard working hours are generally 8:00 a.m. to 4:30 p.m. Eastern Time, Monday through Friday, excluding federal holidays. Occasional work outside normal hours, including evenings, weekends, or holidays, may be required.

Application instructions

To apply, submit your resume through this posting, including a brief summary of your relevant experience and how it maps to the qualifications above.
Reasonable accommodations are available upon request for candidates who need them to participate in the hiring process.

Equal employment opportunity

IGC 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, age, disability, protected veteran status, or any other status protected by applicable law.
Employment is contingent upon contract award and completion of all applicable suitability, verification, and customer-approval requirements.