AI Engineer - Data Science and Algorithms

Maximus is seeking a Lead AI Engineer - Data Science and Algorithms to design, build, deploy, and continuously improve production AI solutions. This is a remote, hands-on individual contributor role for an experienced AI engineer and data scientist who has developed algorithms using real-world data, deployed them into production systems, and supported them throughout their operational lifecycle.

You will work with engineers and technical specialists to solve complex problems using AI, machine learning, mathematics, and data science. The role emphasizes practical algorithm selection, software engineering quality, performance optimization, and responsible AI adoption. You will also help establish reusable technical practices, evaluate emerging technologies, and mentor colleagues working on custom algorithms and AI-enabled solutions., * Lead the development and responsible application of AI, machine learning, mathematical, and data science solutions across the enterprise.

• Apply mathematical analysis and select appropriate tools, technologies, methodologies, processes, and automation to address specific business and technical challenges.
• Design, build, test, deploy, troubleshoot, and improve production AI solutions.
• Take ownership of complex technical problems from initial exploration through implementation and ongoing operational support.
• Write high-quality production software and contribute directly to custom enterprise capabilities.
• Build AI-enabled applications that integrate models, enterprise data, cloud services, APIs, and existing systems.
• Improve solution performance through broader algorithmic enhancements and ongoing optimization.
• Evaluate emerging AI technologies through hands-on experimentation and determine their practical value in production environments.
• Develop reusable components, libraries, design patterns, playbooks, and reference implementations that help other teams deliver AI capabilities.
• Communicate technical requirements, solutions, results, impacts, trade-offs, and risks to technical and non-technical stakeholders.
• Promote initiative, adaptability, and sound engineering judgment when working through ambiguous or fast-changing challenges.
• Maintain current knowledge of AI technologies and assess their suitability for production and operational use.
• Document and share best practices, lessons learned, and technical knowledge across the organization.
• Mentor colleagues through algorithm development, solution design, technical reviews, and improvements to existing capabilities.

• Bachelor’s degree in a relevant field and at least 10 years of relevant professional experience, or an equivalent combination of education and experience.
• At least seven years of professional experience in data science or advanced algorithm development, including substantial experience building and supporting production algorithms that process real-world data.
• At least five years of experience designing or building solutions in cloud environments.
• At least three years of experience with artificial intelligence, machine learning, or related technologies.
• Demonstrated experience developing algorithms, including AI and machine learning algorithms.
• Strong understanding of applying mathematics, AI, and signal processing to production algorithms.
• Experience designing and implementing algorithms on AWS, Microsoft Azure, Google Cloud Platform, or similar cloud platforms.
• Experience deploying algorithms to production systems outside notebook-only environments, such as SageMaker or Jupyter.
• Experience building or integrating AI and machine learning capabilities into software systems.
• Ability to communicate technical decisions, trade-offs, and risks clearly to technical and non-technical colleagues.
• Ability to obtain a Public Trust clearance., * Deep expertise in Python, demonstrated through substantial production software development rather than scripts, notebooks, or prototypes alone.
• Proficiency in at least one systems programming language, such as Rust, Go, C++, or C, with experience applying it to real-world engineering problems.
• Experience building and operating distributed or cloud-native production systems.
• Experience developing algorithms using classical signal processing techniques.
• Experience building AI models from scratch.
• A demonstrated track record of taking algorithms from initial development through production deployment and ongoing operation.
• Experience diagnosing complex production issues across application, infrastructure, data, and integration boundaries.
• Practical experience developing algorithmic solutions using large language models, machine learning models, or managed AI services.
• Experience working in environments where security, privacy, reliability, or regulatory requirements influence engineering decisions.
• Experience improving existing systems where previous technical decisions constrain available options.
• Experience mentoring colleagues through collaboration, design reviews, and technical problem-solving.

• Annual salary range: $180,000-$200,000.

Maximus determines compensation based on factors including work location, education, training, experience, expected work quality and quantity, required travel, external market conditions, internal value analysis, seniority, and merit systems. Compensation may vary with contract value and will reflect job responsibilities and relevant experience. Salary history will not be used to determine compensation.

Additional compensation may include short- and long-term incentives and program-specific awards. Benefits include health insurance, life and disability insurance, a retirement savings plan, paid holidays, and paid time off. Maximus complies with applicable minimum wage requirements and exempt salary thresholds.

Maximus delivers technology-enabled services and supports government programs that serve communities across the United States. Its AI Transformation and Experience team develops and improves enterprise AI capabilities designed to help employees work more effectively and improve the experiences of citizens who rely on government services.