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
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
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.
Skills Required
- Bachelor's degree in Computer Science, Data Science, Software Engineering, Engineering, or a related technical field
- Relevant professional experience in AI engineering, machine learning engineering, or related software engineering roles
- Proficiency in Python
- Familiarity with TensorFlow, PyTorch, and scikit-learn
- Familiarity with MLOps, CI/CD for machine learning, and model monitoring
- 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
- Master's degree
- Experience deploying or supporting machine learning and AI systems in production environments
- Experience working in cloud-based or hybrid technical environments
- Exposure to LLMOps, AIOps, RAG, and vector databases
- 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
What We Do
Since its founding in 1862, ABS has been committed to setting standards for safety and excellence as one of the world’s leading ship classification organizations. We search for and establish the best solutions for the industries we serve, and are at the forefront of marine and offshore innovation. In a constantly evolving industry, ABS works alongside its partners tackling the most pressing technical, operational and regulatory challenges so the marine and offshore industries can operate safely, securely and responsibly. The surveyors, engineers, researches and regulatory specialists who form the ABS team work in more than 200 offices in 70 countries around the world. With a passion for making the world a safer place, while also delivering practical and innovative solutions, ABS stands ready to assist and advance the marine and offshore industries.
