Quantum Sky is seeking a Machine Learning and AI Engineer to join Matrix, the digital platforms team within Project 137, in the Chief Technology Office. Project 137 develops applied research and proprietary technology that support mission needs across the company’s business units. As part of Matrix, you will develop and integrate AI/ML capabilities into digital platforms and enterprise applications.

You will work across machine learning, generative AI, data engineering, and application integration, taking solutions from research and rapid prototyping through evaluation and production deployment. Working closely with Matrix engineers and stakeholders across Project 137, you will help deploy reliable AI capabilities on local hardware and in cloud environments, integrate them with enterprise systems, and communicate their value and limitations.

Responsibilities

• Design, develop, train, evaluate, and deploy machine learning and deep learning models, including computer vision models such as YOLO and model export and serving with ONNX.
• Develop applications using commercial and open-weight large language models (LLMs), deployed on local hardware or in cloud environments.
• Build and optimize retrieval-augmented generation (RAG) pipelines using document ingestion and parsing, embeddings, vector databases, and hybrid keyword and semantic retrieval.
• Implement agentic AI workflows, including tool calling, orchestration, multi-agent coordination, and effective management of model context.
• Evaluate and improve models and AI applications through feature engineering, hyperparameter tuning, prompt design, fine-tuning, and performance optimization.
• Implement AI guardrails for input validation, personally identifiable information (PII), data classification, and safe failure behavior.
• Integrate AI/ML capabilities into production applications and APIs using modular architectures, reusable components, containers, automated testing, and CI/CD pipelines.
• Develop ETL/ELT pipelines for structured and unstructured data; maintain data quality, lineage, and appropriate handling of sensitive information.
• Develop Power BI data models, DAX calculations, advanced analytics, and embedded reporting to make analytical results accessible to users, as needed.
• Integrate solutions with Microsoft Azure services, including Azure OpenAI, and enterprise authentication using Microsoft Entra ID and OAuth.
• Translate ambiguous requirements into technical approaches, research emerging methods, and prototype solutions to assess feasibility before production investment.
• Contribute to architecture, technical planning, code reviews, and documentation; communicate findings to technical and nontechnical audiences.

Required:

• Demonstrated professional experience designing, developing, and supporting production software applications.
• Strong hands-on software development experience with Python, including professional experience developing applications using Django, FastAPI, or a comparable modern framework.
• Programming experience with Go and familiarity with JavaScript/TypeScript or other modern application development languages.
• Experience designing, developing, and consuming RESTful APIs and integrating applications with external systems and services.
• Experience with relational databases, data modeling, backend application architecture, and modern front-end web development technologies.
• Experience building AI agent or agentic-workflow systems: tool use, multi-step orchestration, and integration with large language models.
• Experience with modern front-end development, including at least exposure to generative or AI-driven UI.
• Hands-on experience working in cloud environments such as AWS, GCP, or Azure, with an understanding of how applications are deployed, configured, secured, monitored, and operated in production.
• Experience working within a CI/CD and DevOps-based software delivery environment, including automated builds, testing, deployments, version control, and release processes.
• Familiarity with Infrastructure as Code (Terraform, CloudFormation, or similar), sufficient to work effectively alongside the engineers who own it.
• Experience with Docker, containers, and cloud-native application deployment. Familiarity with Kubernetes or managed container platforms is highly desirable.
• Demonstrated experience using AI-assisted software development tools such as Claude Code, OpenAI Codex, Cursor, GitHub Copilot, or comparable technologies as part of day-to-day professional software development.
• Ability to independently troubleshoot software, integration, deployment, and production issues and develop secure, reliable, and maintainable solutions.
• Comfort operating in a high-ambiguity, early-stage product environment: able to ask clarifying questions, propose trade-offs, and iterate without fully specified requirements.
• Strong analytical, problem-solving, and communication skills with the ability to collaborate across software engineering, product, cloud, and platform teams.

Desired:

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related technical field.
• Direct experience with the Model Context Protocol (MCP) or comparable agent-tool integration standards.
• Experience with agent orchestration frameworks (for example LangChain, LlamaIndex, CrewAI, or comparable).
• Experience developing software for network operations, telemetry, or mission/tactical systems.
• Experience with AWS and/or GCP cloud-native services, including serverless, container, database, messaging, monitoring, identity, and security services.
• Hands-on experience with technologies such as Terraform, Docker, Kubernetes, GitHub Actions, GitLab CI, AWS CodePipeline, CloudFormation, or comparable DevOps and cloud automation technologies.
• Experience with modern JavaScript/TypeScript frameworks (React or similar), including streaming UI patterns.
• Familiarity with vector databases, retrieval-augmented generation, or other applied large-language-model patterns.
• Experience with observability and monitoring platforms such as CloudWatch, OpenSearch, Splunk, Datadog, New Relic, or similar technologies.
• Knowledge of the NIST Risk Management Framework (RMF), NIST SP 800-53 Revision 5, FedRAMP, and FISMA security and compliance requirements.
• Experience translating operational or mission requirements into application features, automation, workflows, integrations, or reporting capabilities.
• Prior experience supporting a Defense Information Systems Agency, Army, Air Force, or other Department of War program.
• Experience developing and operating software supporting federal government, enterprise, or other highly regulated environments.

Clearance: 

• US Citizenship with the ability to obtain a security clearance
• DOD/DoW Secret or Top Secret clearance is preferred

Location:

• Remote, US. Hybrid-remote in Reston, VA (preferred)

Compensation:

• Compensation is unique to each candidate and relative to the skills and experience they bring to the position. The salary range for this position is typically between $135,000 - $155,000. This does not guarantee a specific salary as compensation is based upon multiple factors such as education, experience, certifications, and other requirements, and may fall outside of the above-stated range.

Benefits: