Responsibilities
- Build, train, fine-tune, and optimize machine learning and language models, including multilingual models such as Marian.
- Apply best practices in model training, tuning, optimization, and performance improvement.
- Conduct model evaluation, benchmarking, error analysis, and diagnostics to ensure accuracy and reliability.
- Deploy and scale models using cloud-based AI platforms, with emphasis on AWS SageMaker.
- Integrate AI/ML models into production environments, ensuring interoperability with existing systems.
- Support full-stack development for AI-enabled applications, collaborating with front-end and back-end engineers.
- Work with open-source model libraries, deep learning containers, and GPU-accelerated environments.
- Document workflows, model architectures, and technical designs.
- Collaborate with data scientists, engineers, and product teams to translate mission requirements into technical solutions.
- Participate in occasional on-call support, as needed.
Basic qualifications
- Active TS/SCI w/ Polygraph with this Customer.
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical discipline plus 2 years of relevant experience.
- Hands-on experience developing AI/ML models, particularly language models for NLP applications.
- Proficiency with AI/ML frameworks such as TensorFlow, PyTorch, or Hugging Face.
- Experience with model training, evaluation, and deployment workflows.
- Experience using AWS services such as SageMaker, EC2, S3, and Lambda.
- Strong programming skills in Java, C, and/or C++.
- Familiarity with GPU technologies, deep learning containers, and model optimization techniques.
- Understanding of full-stack development concepts and system integration.
- Strong analytical, problem-solving, and communication skills.
- Ability to work effectively in a collaborative, mission-focused environment.
Preferred qualifications
- Experience with computational linguistics.
- Experience with Large Language Models (LLMs).
- Experience with model versioning and management tools such as MLflow or Git.
- Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
- Experience working in a government or defense-related environment.
- Experience with secure data handling and compliance requirements.
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Ai Ai Engineer Machine Learning Nlp