AI/ML Engineer

ABS Group is seeking an AI/ML Engineer to join our Artificial Intelligence Practice in support of a major federal modernization program. In this role, you will design, develop, and operationalize machine learning and artificial intelligence solutions that support mission applications and data-driven workflows. 

You will help bring AI capabilities into production, build supporting pipelines and model operations workflows, and work across data science, engineering, and cloud teams to deliver scalable, secure, and trustworthy AI solutions. The scope of responsibility, degree of technical leadership, and level of independence expected will reflect the level at which this position is filled. 

What You Will Do 

• Design, develop, and operate AI and machine learning capabilities for production applications and data workflows 

• Build and maintain data and model pipelines that support training, deployment, monitoring, and lifecycle management 

• Partner with data scientists, developers, and cloud engineers to productionize AI solutions 

• Implement MLOps and related engineering practices for model deployment, monitoring, retraining, and version control 

• Support generative AI and large language model implementations, including prompt workflows, retrieval-augmented generation, and vector-based retrieval patterns 

• Apply AI/ML to adjacent use cases such as test automation, workflow support, and operational optimization 

• Contribute to CI/CD, observability, and operational support for AI systems in secure environments 

• Support responsible AI and model governance practices, including explainability and compliance requirements 

• Document architectures, workflows, and engineering standards for project delivery 

What You Will Need 

Level and Compensation: This position may be filled at multiple career levels based on business need and the selected candidate's qualifications, relevant experience, and demonstrated capability. Typical leveling for this role is as follows:

• Junior (0 to 4 years)

• Mid-Level (5 to 9 years)

• Senior (10 to 14 years)

• Principal (15 or more years)

These ranges are guidelines only and are not the sole determining factor in level. The posted compensation range reflects the full range across all possible levels. Individual offers will be based on the level at which the candidate is hired, as well as factors such as skills, experience, internal equity, and geographic market considerations where applicable. 

Education and Experience 

• Bachelor's degree in Computer Science, Data Science, Software Engineering, Engineering, or a related technical field; Master's degree preferred 

• Relevant professional experience in AI engineering, machine learning engineering, or related software engineering roles; the depth and scope of experience required will vary based on the level at which this position is filled 

• Experience deploying or supporting machine learning and AI systems in production environments preferred 

• Experience working in cloud-based or hybrid technical environments preferred 

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Knowledge, Skills, and Abilities 

• Proficiency in Python 

• Familiarity with frameworks such as TensorFlow, PyTorch, and scikit-learn 

• Familiarity with MLOps, CI/CD for ML, and model monitoring concepts and practices 

• Exposure to LLMOps, AIOps, RAG, and vector databases 

• Experience building or supporting data pipelines for AI/ML applications 

• Understanding of software engineering and DevSecOps practices for production systems 

• Strong collaboration skills across technical teams and stakeholders 

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Nice to Have 

• Experience supporting production ML at scale 

• Experience with AWS, Azure, or GCP AI/ML services 

• Familiarity with federal, public sector, or regulated AI environments 

• Exposure to NLP, classification, survey analytics, or entity resolution use cases 

Location 

This position is based in the Washington, D.C. metro area, with primary work performed in Suitland, Maryland. Remote or hybrid arrangements may be available for eligible work, subject to government approval.