Android Ai Ml Engineer Infrastructure Jobs (NOW HIRING)

Job Summary:
Assured Consulting Solutions is a company that provides strategic and innovative solutions for customer needs across the business, technology, and organizational spectrum. They are seeking an experienced AI/ML Engineer to develop and implement AI/ML capabilities for mission-critical problems, focusing on model training and deployment. The role involves collaborating with stakeholders to translate operational needs into technical designs and optimizing machine learning models.
Responsibilities:
• Develop and automate fine-tuning and model training pipelines using available tools or custom code.
• Develop innovative AI/ML and LLM-enabled solutions to address specific mission challenges and operational needs.
• Design, implement, and optimize machine learning models for new mission-critical use cases and features.
• Conduct research on novel modeling approaches, architectures, and techniques to maximize mission capability and competitive advantage.
• Work with mission leads and stakeholders to translate operational needs into technical AI/ML designs and implementation plans.
• Build and maintain MLOps and model deployment pipelines for experiment tracking, model versioning, and reliable production releases.
• Define and track model performance metrics aligned to mission success criteria and use evaluation findings to drive improvements.
• Integrate AI/ML model services into application workflows through APIs and production-ready interfaces.
• Partner with Data Integration Engineers to utilize curated training datasets, test corpora, and evaluation frameworks.
• Collaborate with Senior Software Engineers to operationalize AI/ML capabilities within secure, mission-focused application environments.
• Implement guardrails, monitoring, and fallback strategies for responsible and reliable AI/ML-enabled operations.
• Analyze model behavior, identify performance gaps, and innovate on approaches to improve quality, reliability, and mission impact.
• Document model designs, assumptions, training methodologies, evaluation results, and operational guidance for sustainability and knowledge transfer.
• Support production troubleshooting and performance optimization for mission-critical model-serving workloads.
• Contribute to technical standards and best practices for responsible, secure AI/ML engineering in mission environments.
Qualifications:
Required:
• Bachelor's degree or higher in a related STEM field, or equivalent experience
• Hands-on experience in machine learning engineering, applied AI, or model development with demonstrated model deployment to production.
• Strong software engineering skills in Python for model development, training, inference, and experimentation workflows.
• Experience developing and evaluating machine learning models (supervised, unsupervised, or reinforcement learning) in production or mission-focused contexts.
• Demonstrated experience implementing and operationalizing LLM-enabled applications or features, including prompting strategies, retrieval approaches, and integration patterns.
• Experience building and maintaining MLOps infrastructure, including experiment tracking, model versioning, reproducibility, and continuous deployment practices.
• Experience defining model performance metrics, conducting model evaluation, and using evaluation results to drive improvements.
• Experience deploying and operating model services in containerized environments (for example OpenShift or Kubernetes).
• Demonstrated case studies or examples of innovative use of AI/ML to solve domain-specific or mission-critical problems.
• Demonstrated ability to communicate technical complexity, model assumptions, and performance limitations clearly to both technical and non-technical stakeholders.
• Understanding of secure development, secure AI practices, and deployment governance in controlled or classified environments.
Preferred:
• Experience supporting DIA or comparable intelligence community mission environments and problem sets.
• Experience with AWS and C2E cloud environments for AI/ML workload and model serving.
• Experience with advanced model-serving frameworks, orchestration, or inference optimization.
• Familiarity with ontology-driven data modeling or semantic technologies (for example RDF, OWL, or knowledge graphs) for structured reasoning.
• Experience with retrieval-augmented generation (RAG), vector search, knowledge-grounded LLM approaches, or semantic search.
• Experience with multi-model or ensemble approaches for improved performance or robustness.
• Familiarity with DevSecOps practices and model release governance in secure environments.
• Experience evaluating and improving reliability, observability, and performance monitoring for mission-critical AI systems.
Company:
Rewarding Work. Generous Benefits. Committed to You. Founded in 2011, the company is headquartered in Fairfax, USA, with a team of 51-200 employees. The company is currently Growth Stage.