Machine Learning Engineer

Machine Learning Engineer

Job ID: 2615287

Location: Chantilly, VA, United States

Date Posted: Aug 5, 2026

Category: Information Technology

Subcategory: Data Scientist

Schedule: Full-Time

Shift: Day Job

Travel: No

Minimum Clearance Required: TS/SCI with Poly

Clearance Level Must Be Able to Obtain: None

Potential for Remote Work: On-Site

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Job Description

Description

SAIC is seeking a skilled Machine Learning Engineer to design, develop, and deploy machine learning (ML) models tailored to diverse applications, while delivering innovative solutions under tight deadlines. The ideal candidate will possess expertise in Docker and containerization, with the ability to build and deploy ML models and tools in offline, standalone environments.

Key Responsibilities:

• Research and evaluate open-source ML models, fine-tuning them to meet specific operational needs.

• Design and develop custom Python-based applications (desktop and web-based) for hosting ML models.

• Experience with web-based platforms such as ComfyUI, Gradio, and Streamlit is preferred.

• Apply a solid understanding of digital signal processing (DSP) to build effect chains that transform signals to achieve desired outcomes.

• Provide rapid responses to evolving operational requirements, executing agile development to deliver customized solutions.

• Collaborate with a multidisciplinary team to address mission-critical objectives through innovative approaches.

• Leverage data science techniques to evaluate datasets, identify trends, and inform decision-making.

Required Skills & Experience:

• Proficiency in Docker for building and managing containers.

• Strong knowledge of Python programming with a focus on ML application development.

• Familiarity with DSP techniques and their practical application in signal transformation.

• Experience developing and hosting ML models using both desktop and web-based interfaces.

• Ability to work effectively in a fast-paced environment, responding to ad-hoc requests with innovative problem-solving.

Join our dynamic team to contribute cutting-edge ML solutions for high-impact projects. Your work will directly support critical mission operations in a challenging, fast-evolving environment.

Qualifications

REQUIRED:

• Must be a US Citizen

• Must have an active TS/SCI with Poly clearance

• Bachelor''s degree in computer science, math, data science or another technical/scientific field.

• Expertise with Python

• ML Frameworks (pytorch, tensorflow, onnx)

• Model hosting frameworks (ComfyUI, steamlit, gradio, FastAPI)

• Data science libraries (Pandas, Numpy, SciKit-learn, Scipy, matplotlib/seaborn)

• App Dev Frameworks (PyQt, tkinter)

• Experience with Docker

• Familiarity with Linux

• Familiarity with Windows OS

• Experience with version control software (Git)

DESIRED:

• Audio hardware familiarity

• Audio engineering/digital processing (DSP) familiarity

• Kubernetes familiarity

• Rancher

• Longhorn

• ArgoCD

• Matlab

• C++ (Cython wrapper around C++ application)

Target salary range: $200,001 - $240,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.

Overview

SAIC accepts applications on an ongoing basis and there is no deadline.

SAIC is a premier mission integrator focused on advancing the power of technology and innovation to serve and protect our world. Our robust portfolio of offerings across the defense, space, intelligence, and civilian markets includes secure high-end solutions in mission IT, enterprise IT, engineering services, and professional services. We integrate emerging technology, rapidly and securely, into mission critical operations that modernize and enable critical national imperatives.

We are approximately 23,000 strong; driven by mission, united by purpose, and inspired by opportunities. SAIC is an Equal Opportunity Employer. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $7.3 billion. For more information, visit saic.com. For ongoing news, please visit our newsroom.

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