AI/ML Engineer I

Reflexive Concepts•Annapolis Junction, MD

About The Position

Reflexive Concepts is seeking an AI/ML Engineer to work across the machine learning model development lifecycle and collaborate with cross-functional teams to deliver high-impact solutions. The role focuses on natural language processing and language models, including multilingual model development, while also contributing to full-stack development for AI model-based applications. The engineer will build, train, fine-tune, evaluate, optimize, deploy, and integrate machine learning models. The role also involves developing and maintaining application front ends and back ends, contributing to scalable deployment pipelines, translating business requirements into technical solutions, and documenting workflows, model designs, and technical specifications. The position may include occasional on-call duties.

Requirements

At least 2 years of applied machine learning experience on programs and contracts of similar scope, type, and complexity.
A bachelor’s degree in advanced mathematics, computer science, or a related STEM discipline from an accredited college or university, or 3 additional years of machine learning experience on projects with similar machine learning processes in lieu of the degree.
Knowledge and experience with language models.
Specific experience with Marian and multilingual model development.
Strong proficiency in AI/ML frameworks such as TensorFlow, PyTorch, or Hugging Face.
Expertise in model training, evaluation, and deployment.
Hands-on experience with AWS SageMaker, Lambda, EC2, and S3.
Experience developing full-stack software applications using technologies such as JavaScript, Python, or Java.
Strong Java, C, and C++ programming experience.
Solid understanding of data structures, algorithms, and system design.
Experience with machine learning model development, including natural language processing.
Experience with model evaluation, optimization, and performance monitoring.
Proven software engineering experience and strong coding skills.
Strong problem-solving and analytical skills.
Excellent communication and collaboration abilities.

Nice To Haves

Knowledge of computational linguistics.
Experience with open-source model libraries, Deep Learning Containers (DLC), GPU technologies, and optimization or tuning.
Experience in a government or defense-related environment.
Experience with model versioning and management tools such as MLflow or Git.
Familiarity with containerization tools such as Kubernetes.
Experience with secure data handling and compliance requirements.
Experience working with large language models (LLMs).
Willingness to support occasional on-call duties.

Responsibilities

Build, train, and fine-tune machine learning models, particularly language models.
Apply best practices in model training, tuning, and optimization.
Design and implement solutions to improve model performance.
Conduct model evaluation, performance analysis, and benchmarking.
Perform error analysis, debugging, and model diagnostics to ensure quality and reliability.
Use cloud-based AI platforms, especially AWS SageMaker, to deploy and scale models.
Integrate machine learning models into production environments and ensure they work seamlessly with other systems.
Contribute to the development and maintenance of the front end and back end of AI model-based applications.
Collaborate with software engineers to build scalable and efficient deployment pipelines.
Work with data scientists, product teams, and engineers to translate business requirements into technical solutions.
Document workflows, model design processes, and technical specifications.
Support occasional on-call duties, if needed.