> Markdown version of [/jobs/ext/1950207-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/1950207-machine-learning-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Machine Learning Engineer

- **Company:** Science Applications International Corporation
- **Location:** Chantilly, VA, United States
- **Salary:** $200,001.0 - $240,000.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, C++ (Programming Language), Computer Programming, Linux, Python (Programming Language), MATLAB, Machine Learning, NumPy, Open Source Technology, Tensorflow, SciPy, Software Engineering, Standard Widget Toolkits, Web Applications, Windows Desktop, Pytorch, Git, Fastapi, Pandas, Matplotlib, Build Management, Containerization, Scikit Learn, Kubernetes, Information Technology, ONNX (Open Neural Network Exchange) Format, Rancher, Streamlit Framework, Software Version Control, Docker
- **Published:** August 6, 2026
- **Apply:** https://www.careerarc.com/job-listing/saic-jobs-machine-learning-engineer-52913403

## About the Role

* 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., * 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)

## 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.


## Related Videos

- [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops)
- [Vectorize all the things! Using linear algebra and NumPy to make your Python code lightning fast.](https://www.wearedevelopers.com/videos/562-vectorize-all-the-things-using-linear-algebra-and-numpy-to-make-your-python-code-lightning-fast)
- [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker)
- [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94)
- [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning)
- [How to implement convenient Python bindings to C++](https://www.wearedevelopers.com/videos/618-how-to-implement-convenient-python-bindings-to-c)

## Related Articles

- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)
- [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)
- [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)
- [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)
- [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)
- [ Dev Digest 213: Petrol Prices, Agentic Workflows, AI Skills and CODE100!](https://www.wearedevelopers.com/magazine/718-dev-digest-213-petrol-prices-agentic-workflows-ai-skills-and-code100)