Artificial Intelligence and Machine Learning Engineer, Mid

Booz Allen Hamilton

Quick summary

Work type
On-site
Location
McLean, VA
Salary
$77,600–$176,000 / yr
Posted
11 days ago
Closes
Jun 30, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $217k
This role $127k
$56k most similar roles pay here $283k

This role pays less than 98% of similar roles. Most pay $184,975–$249,750 — the shaded band above. At the midpoint, this role pays about $127k versus about $217k for comparable roles.

Based on 240 similar postings.

Employer

About Booz Allen Hamilton

Booz Allen Hamilton is a management and technology consulting firm that provides analytics, digital, engineering, and cybersecurity solutions primarily to U.S. government agencies and commercial clients. Industry: Management & Technology Consulting

Booz Allen Hamilton currently has 375 open roles on FindRole.

Listed pay typically runs $86,800–$198,000 across 368 roles with salary data.

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View all roles at Booz Allen Hamilton

At a glance

TL;DR · Artificial Intelligence and Machine Learning Engineer, Mid

As a mid-level Artificial Intelligence and Machine Learning Engineer, you will join a cross-functional team to develop and operationalize secure, scalable AI solutions using Databricks, Palantir, Amazon Bedrock, and custom models. Your daily tasks include modernizing data pipelines, enhancing data quality and observability, and integrating rules-driven scoring systems with human-in-the-loop review processes. You will build production-grade ML pipelines with MLOps practices like versioning, CI/CD, monitoring, and fairness assessments, while ensuring compliance with security standards such as ATO in a regulated cloud environment. This role requires experience with Python, scikit-learn, PyTorch, TensorFlow, and API-first integration patterns, along with knowledge of responsible AI principles and documentation skills for architecture artifacts and operational runbooks.

What you'll do

  • Develop and operationalize secure, scalable AI solutions for mission-critical capabilities.
  • Modernize and operate an end-to-end AI-driven platform using Databricks, Palantir, Amazon Bedrock, and custom models.
  • Improve data quality, lineage, and observability in enterprise environments.
  • Build production-grade ML pipelines with MLOps practices including versioning, CI/CD, monitoring, and explainability.
  • Decompose legacy case selection capabilities into scalable services for operationalization.
  • Integrate AI solutions with shared enterprise services using API-first and event-driven patterns.

What we're looking for

  • Experience building, deploying, and operating production ML models including supervised, unsupervised, and anomaly detection.
  • Proficient in MLOps practices such as model versioning, CI/CD for ML, monitoring, drift detection, and automated retraining.
  • Expertise with Python and ML frameworks like scikit-learn, PyTorch, or TensorFlow.
  • Experience with data engineering platforms including Databricks, Spark, SQL, and batch/streaming pipelines.
  • Knowledge of responsible AI practices, including explainability, fairness, and bias assessment.
  • Ability to design architecture artifacts, data contracts, and operational runbooks for secure service-to-service communication.

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