reflexiveconcepts.catsone.com
AI/ML Engineer I
AI/ML Engineer I building and deploying NLP/language models across the full lifecycle — training, fine-tuning, evaluation, and deployment on AWS (SageMaker) — plus full-stack integration of model-based applications. Requires applied ML experience and strong Java, C, C++, and Python skills.
- Compensation
- Not disclosed
- Location
- Annapolis Junction, MD
- Work setup
- Not specified
- Seniority
- Junior
- Employment
- Not specified
- Experience
- 2+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- 2 years of experience in applied machine learning on programs and contracts of similar scope, type, and complexity
- B.S. in advanced math (calculus, linear algebra, Bayesian statistics), computer science, or related STEM discipline
- Knowledge and experience with language models
- Specific experience with Marian and multi-lingual model development
- Experience with open-source model libraries, Deep Learning Containers (DLC), GPU technologies, and optimization/tuning
- Strong Java, C, C++ programming experience
- 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 tools like SageMaker, Lambda, EC2, and S3
- Experience developing full-stack software applications (JavaScript, Python, Java, etc.)
- Solid understanding of data structures, algorithms, and system design
- Extensive experience in machine learning model development, including NLP
- Experience with model evaluation, optimization, and performance monitoring
- Proven experience in software engineering with strong coding skills
- Experience with model versioning and management using tools such as MLflow or Git
- Strong problem-solving and analytical skills
- Excellent communication and collaboration abilities
Nice to have
- 3 years of additional ML experience on similar projects may be substituted for the bachelor's degree
- Knowledge of computational linguistics
- Willingness to support occasional on-call duties
- Experience working in a government or defense-related environment
- Familiarity with containerization tools such as Kubernetes
- Experience with secure data handling and compliance requirements
- Experience working with Large Language Models (LLMs)
Full description
Reflexive Concepts is seeking a skilled Artificial Intelligence/Machine Learning I to join our team!
The ideal candidate will have hands-on experience with state-of-the-art machine learning techniques, specifically for natural language processing (NLP), and will also have a strong understanding of full-stack development. This person will work across the model development lifecycle and collaborate with cross-functional teams to deliver high-impact solutions.
Qualifications:
- 2 years of experience in applied machine learning in programs and contracts of similar scope, type, and complexity is required.
- B.S. degree in advanced math (e.g., calculus, linear algebra or Bayesian statistics), computer science or related STEM discipline from an accredited college or university is required.
- 3 years of additional machine learning experience on projects with similar machine learning processes may be substituted for a bachelor’s degree.
Key Responsibilities:
- Knowledge and experience of Language models is required
- Specific experience with Marian and multi-lingual model development
- Knowledge of Computation Linguistics is a plus
- Experience with Open-Source model libraries, Deep Learning Containers (DLC), GPU technologies and optimization / tuning
- Strong Java, C, C++ programming experience
- Willingness to support occasional on-call duties is a plus
- Model Development & Training:
- Build, train, and fine-tune machine learning models, particularly language models
- Apply best practices in model training, tuning, and optimization.
- Design and implement solutions for model performance improvement.
- Evaluation & Testing:
- Conduct rigorous model evaluation, including performance analysis and benchmarking.
- Perform error analysis, debugging, and model diagnostics to ensure quality and reliability.
- Model Deployment & Integration:
- Work with cloud-based AI platforms (especially AWS Sagemaker) to deploy and scale models.
- Integrate machine learning models into production environments, ensuring seamless integration with other systems.
- Full-Stack Engineering:
- Contribute to the development and maintenance of the full stack for AI model-based applications (front-end and back-end).
- Collaborate with software engineers to build scalable and efficient deployment pipelines.