Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI/ML): Developing and optimizing ML models and scalable training pipelines for US Government agency services with an accent on LLMs, RAG, and AI agent systems. Focus on productionizing models using MLOps practices on AWS and Databricks to ensure system reliability and scalability.

Location: Remote (Must be based in the USA, specifically tied to Vienna, VA)

Salary: $140,000 - $150,000 per year

Company

hirify.global Corp provides digital services, advanced analytics, AI/ML, and cybersecurity services to numerous US government executive and independent agencies.

What you will do

• Collaborate with data scientists and SMEs to develop and validate ML models using curated datasets.
• Build scalable and reusable training pipelines using Databricks notebooks and MLflow.
• Implement LLMs, RAG, and AI agent systems for various business applications.
• Operationalize models with robust CI/CD workflows using SageMaker or custom APIs.
• Align ML pipelines with the Medallion Architecture (Bronze, Silver, Gold layers).
• Mentor junior team members and document ML artifacts, processes, and outcomes.

Requirements

• 5+ years of experience in ML Engineering or Applied Machine Learning.
• Advanced programming skills in Python and hands-on experience with scikit-learn, PyTorch, or TensorFlow.
• Proficiency with Databricks, MLflow, and PySpark.
• Experience with AWS-based data infrastructure (S3, EC2, Lambda, SageMaker, Step Functions).
• Practical experience with LLMs, RAG, and AI agent architectures.
• Must be authorized to work in the US for government agency contracts.

Nice to have

• Experience building interactive UIs for AI models using Streamlit or Gradio.
• Business acumen to align AI solutions with organizational goals.
• Ability to optimize compute and storage resources for performance and cost-efficiency.

Culture & Benefits

• Opportunity to work with a successful WOB business holding 50+ prime contracts.
• Engagement with cutting-edge technology across the US Government sector.
• Collaborative environment with a focus on knowledge sharing and mentorship.
• Equal opportunity employer commitment.