AI/ML Engineer

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AI/ML Engineer

Finch Computing

180,000–250,000 / Year

Location

McLean, VA

Experience

Senior

Posted

Jul 7, 2026

Apply by

August 6, 2026

Applicants

0

Early applicantEasy applyFull-timeWork from Office

Job Description

**AI/ML Engineer** **Clearance:** Must hold an existing active TS/SCI with required polygraph (US Citizenship required) **Location:** McLean, VA Onsite Daily **Salary:** 180,000-250,000 Commensurate with experience **Responsibilities:** - Implement and maintain RAG pipelines, including document processing, embedding generation, retrieval configuration, and prompt assembly. - Integrate LLMs into applications using available APIs and frameworks. - Develop and maintain REST API interactions to support data retrieval and system integration. - Design or refine Postgres schemas to improve data organization and query performance. **Requirements:** - Demonstrated ability to conduct independent technical research, evaluate emerging AI/ML approaches, and apply advanced analytical problem-solving comparable to PhD-level research environments. - Ability to rapidly learn and apply new AI/ML methodologies, tools, and frameworks in support of evolving mission requirements. - Experience developing AI/ML applications focused on Retrieval-Augmented Generation (RAG), semantic retrieval, LLM integration, or related AI workflows. - Strong proficiency in Python and modern AI/ML libraries, frameworks, and API integrations. - Active/current TS/SCI with required polygraph (US citizenship required) - Willingness to work onsite full time. **Preferred Skills:** - Advanced research experience in machine learning, deep learning, natural language processing, generative AI, reinforcement learning, computer vision, or related disciplines. - Experience publishing research, contributing to open-source AI/ML initiatives, or leading experimental and prototype development efforts. - Familiarity with model evaluation frameworks, fine-tuning workflows, inference optimization, and AI observability/monitoring tools. - Experience with vector databases, AWS/cloud environments, Docker, and containerized AI/ML development workflows. - Experience designing and integrating REST APIs and scalable data architectures. **Education and Work Experience:** - 8 years of experience with a Bachelor’s degree; or 7 years of experience with a Masters degree; or 6 years of experience with a Doctorate **About FINCH AI** Finch AI is a fast-growing, fast-paced software development organization; our mission is to build new ways of interacting with information. We do that by leveraging game-changing intellectual property, cloud infrastructure expertise, and a staff that is second to none. Together, we build and support products that address complex, real-time data and analytics needs in the enterprise. Our teams are comprised of successful people that enjoy solving problems, engaging in substantive technical discussions and have passion for their work. We have very high expectations in terms of skill, motivation, self-organization and productivity. We look for people who excel working in groups, virtual and collocated, as well as those who are comfortable with fast paced agile development. Finch AI is an equal opportunity employer.

Key Responsibilities

  • Implement and maintain RAG pipelines including document processing, embedding generation, and prompt assembly.
  • Integrate LLMs into applications using available APIs and frameworks.
  • Develop and maintain REST API interactions for data retrieval and system integration.
  • Design or refine Postgres schemas to improve data organization and query performance.

Requirements

  • Bachelor's degree with 8 years of experience
  • Master's degree with 7 years of experience
  • Doctorate with 6 years of experience

Skills Required

PythonRAGLLM IntegrationREST APIPostgreSQLSemantic RetrievalIndependent technical researchAnalytical problem-solvingRapid learningSelf-organizationProductivityMachine LearningDeep LearningNatural Language ProcessingGenerative AIReinforcement LearningComputer VisionVector DatabasesAWSCloud EnvironmentsDockerContainerized AI/ML DevelopmentModel Evaluation FrameworksFine-tuning WorkflowsInference OptimizationAI Observability ToolsResearch ExperienceOpen-source ContributionPrototype Development

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