Mid AI/ML Engineer
$143,763–$143,763 year
On-siteWashington, United States
Job Summary
Develop and optimize ML models, pipelines, and platform components while building RAG architectures and high-performing inference systems. Create scalable infrastructure for training, experimentation, and deployment, then lead integration of these models into production environments. Conduct advanced troubleshooting and performance tuning to ensure system reliability. Collaborate with stakeholders to accelerate mission-driven insights within a federal enterprise multi-domain data ecosystem. Operate with autonomy to influence major technical deliverables while adhering to larger team project management standards. This role requires Secret or TS/SCI clearance and is based in the National Capital Region with potential for hybrid telework.
Required Qualifications
- Deep experience building LLM-based systems and RAG architectures
- Strong proficiency in MLOps tools (e.g. MLFlow, Kubeflow, Airflow)
- Advanced scripting (e.g. Python, JavaScript, Rust)
- Expertise deploying models on AWS, Azure, or GCP
- Ability to work independently with broad responsibilities
- Bachelor's degree in CS, engineering, mathematics, or related field
- 3+ years AI/ML professional experience
- Intermediate certifications (CCSP, CFR, FITSP-M, GSEC, Security+, SSCP) or advanced certifications (SecurityX / CASP+, GCSA, GSLC, CISSP)
- U.S. Citizen — Secret or TS/SCI eligible
- On client site with potential for hybrid telework
Desired Qualifications
- Experience with scientific datasets or multi-domain research workflows
- Familiarity with AWS Bedrock, Databricks, vector databases or comparable technologies
- Strong foundation in prompt engineering or AI agents
- Experience working with federal clients
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