Build and deploy AI solutions that move from “cool model” to real mission outcomes for a federal agency client. If you can design ML and deep learning systems, operationalize them with strong MLOps, and translate technical work into plain-English impact, this role is built for you.
About Maximus
Maximus supports public-sector clients with technology delivery and modernization, including advanced analytics and AI initiatives. In this role, you’ll help shape responsible AI/ML solutions, contribute to reusable playbooks and best practices, and collaborate across engineers and data scientists to put models into production.
Schedule
- Full-time, fully remote
- Washington, DC area candidates preferred
- Requires federal background investigation (interim clearance required before starting)
- Must be a U.S. Citizen or a Legal Permanent Resident (Green Card) for at least 3 years to be eligible for the clearance process
What You’ll Do
- Design, develop, and deploy machine learning and deep learning models to support business objectives
- Build, test, and implement end-to-end model workflows, including data prep and automation
- Partner with software engineers and data scientists to integrate trained models into scalable production environments
- Use Python (and working knowledge of R and other languages as needed) to develop pipelines, preprocessing, and model automation routines
- Apply data structures, algorithms, and statistics to improve model accuracy, efficiency, and reliability
- Work with large language model platforms (ChatGPT, Gemini, or Meta LLMs), including OpenAI API integration and prompt optimization
- Apply or contribute to integration approaches such as LangChain products, MCP, and connections to databases/knowledge artifacts (preferred)
- Implement and maintain MLOps practices for continuous training, deployment, monitoring, and iteration
- Evaluate emerging AI tools, frameworks, and methods to improve system performance and delivery speed
- Translate business needs into technical solutions and communicate outcomes to technical and non-technical stakeholders
- Document system design, model performance, and workflows for reproducibility and future improvements
- Create and promote playbooks, best practices, lessons learned, and internal intellectual capital
What You Need
- Bachelor’s degree in a relevant field and 7+ years of relevant experience, or equivalent combination of education and experience
- 10+ years of professional software engineering experience (Java, Python, R, or similar)
- 2+ years of current hands-on experience in:
- Data mining, machine learning, deep learning (neural networks)
- Data structures, algorithms, statistics, and model training
- Practical experience with Python and frameworks such as PyTorch and TensorFlow
- Experience with at least one LLM platform (ChatGPT, Gemini, Meta LLMs) and strong understanding of OpenAI APIs and integration
- Strong communication skills and ability to translate technical work to all audiences
- Ability to work independently, manage time well, and collaborate effectively across teams
- Ability to obtain and maintain a federal background investigation clearance
Benefits
- Health insurance coverage
- Retirement savings plan
- Paid holidays and paid time off
- Life and disability insurance
- Additional incentives may be available based on program/role
Clearance-driven AI roles don’t stay open forever, and the background process can be a gate—apply early to get your place in line.
If you’re the kind of engineer who can ship models, not just prototype them, this is a strong fit.
Happy Hunting,
~Two Chicks…