AI/ML Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and implement AI/ML capabilities that enhance mission workflows utilizing FedRAMP-authorized services available in AWS GovCloud, covering data preparation, deployment, evaluation, and monitoring.

• Design, construct, test, and operationalize AI/ML solutions that meet established mission and business requirements.

• Convert operational use cases into scalable AI/ML architectures, services, and integration patterns.

• Create APIs, services, and application integrations that expose AI/ML functionalities to mission applications and enterprise systems.

• Work closely with application engineers, data engineers, cloud engineers, cybersecurity teams, and mission stakeholders throughout the entire solution lifecycle.

• Perform technical evaluations and proof-of-concept implementations of AI/ML technologies.

• Maintain comprehensive technical documentation that includes architecture, model behavior, interfaces, dependencies, deployment procedures, and operational requirements.

• Build production-quality AI/ML applications and supporting services using Python.

• Develop reusable Python modules, services, utilities, and automation for data processing, inference, evaluation, and system integration.

• Implement source control, automated testing, code reviews, dependency management, and CI/CD practices.

• Create and integrate machine learning models, foundation models, or AI services.

• Enhance the performance, reliability, scalability, and resource utilization of AI/ML applications.

• Diagnose model behavior, data quality, application integration, cloud services, and runtime issues.

• Design and execute Generative AI and Retrieval-Augmented Generation (RAG) patterns.

• Develop workflows for document ingestion, parsing, chunking, embedding, indexing, retrieval, prompt construction, and model inference.

• Integrate approved large language models and foundation-model services with enterprise applications and mission data sources.

• Assess retrieval quality, response relevance, groundedness, hallucination risk, and overall solution effectiveness.

• Create prompt management, model routing, and orchestration patterns.

• Implement safeguards and validation mechanisms to mitigate inappropriate, inaccurate, or unauthorized model outputs.

• Facilitate secure integration of vector stores, search services, knowledge repositories, and other RAG components.

⛳️ Requirements

• A Bachelor’s degree in Cybersecurity, Computer Science, Information Technology, Information Systems, or a related technical field.

• Experience with Generative AI, foundation models, and RAG architectures relevant to the program scope.

• Proficiency in embeddings, vector search, semantic retrieval, prompt engineering, and LLM evaluation.

• Experience in supervised or unsupervised machine learning, feature engineering, model training, and model selection, especially where traditional ML applies.

• Knowledge of MLOps or LLMOps practices for managing model and application lifecycles.

• Experience in developing automated frameworks for model and application evaluation.

• Familiarity with responsible AI principles, including model limitations, bias evaluation, explainability, traceability, and human oversight.

• Experience in deploying containerized workloads and microservices.

• Experience in government, defense, regulated, or other security-sensitive environments.

• Preferred certifications include AWS Certified AI Practitioner; AWS Certified Machine Learning Specialty.

🏝️ Benefits

• Competitive salary, paid bi-monthly.

• Comprehensive medical coverage.

• 100% of medical premiums covered by True Zero.

• Company-wide incentives for new business initiatives.

• Contribution Incentives (e.g., white papers, blog posts, internal webinars, etc.).

• 3 weeks of paid time off (PTO) plus 11 paid holidays annually.

• 401k program with a 100% company match on the first 4% contributed.

• Monthly reimbursement for cell phone and home internet expenses.

• Paternity and maternity leave.

• Investment in training and certifications to enhance and expand your technical skills.