> Markdown version of [/jobs/ext/4626294-artificial-intelligence-machine-learning-1-fst-148](https://www.wearedevelopers.com/jobs/ext/4626294-artificial-intelligence-machine-learning-1-fst-148). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Artificial Intelligence Machine Learning 1 (FST - 148) - **Company:** Sagecor Solutions (sagecor) - **Location:** Cape Saint Claire, MD, United States - **Contract:** Permanent contract - **Skills:** C (Programming Language), Java (Programming Language), JavaScript (Programming Language), Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, C++ (Programming Language), Data Security, Data Structures, Software Debugging, Python (Programming Language), Machine Learning, Language Modeling, Natural Language Processing, Open Source Technology, Performance Tuning, Tensorflow, Software Engineering, Pytorch, Delivery Pipeline, Large Language Models, Deep Learning, Model Validation, Backend, Git, Containerization, Kubernetes, HuggingFace, Performance Monitor, Machine Learning Operations, Front End Software Development, Functional Programming, Software Coding, Software Version Control - **Published:** November 7, 2026 - **Apply:** https://www.dice.com/job-detail/ed801464-b964-4b1e-93ee-fd84edccfb0f ## About the Role Knowledge and experience of Language models is required o 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, o Strong proficiency in AI/ML frameworks such as TensorFlow, PyTorch, or Hugging Face. o Expertise in model training, evaluation, and deployment. o Hands-on experience with AWS tools like SageMaker, Lambda, EC2, and S3. o Experience in developing full-stack software applications (JavaScript, Python, Java, etc.). o Solid understanding of data structures, algorithms, and system design. Experience & Background: o Extensive experience in machine learning model development, including natural language processing (NLP). o Experience with model evaluation, optimization, and performance monitoring. o Proven experience in software engineering with strong coding skills. o Experience working in a government or defense-related environment is highly preferred. Additional Skills: o Experience with model versioning and management using tools such as MLFlow or Git. o Familiarity with containerization tools (i.e. Kubernetes). o Strong problem-solving and analytical skills. o Excellent communication and collaboration abilities. Nice to Have: Experience with secure data handling and compliance requirements Experience working with Large Language Models (LLMs) Consistent with federal and state law where SageCor conducts business, SageCor Solutions provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, or any other protected class. ## Description o Build, train, and fine-tune machine learning models, particularly language models o Apply best practices in model training, tuning, and optimization. o Design and implement solutions for model performance improvement. Evaluation & Testing: o Conduct rigorous model evaluation, including performance analysis and benchmarking. o Perform error analysis, debugging, and model diagnostics to ensure quality and reliability. Model Deployment & Integration: o Work with cloud-based AI platforms (especially AWS Sagemaker) to deploy and scale models. o Integrate machine learning models into production environments, ensuring seamless integration with other systems. Full-Stack Engineering: o Contribute to the development and maintenance of the full stack for AI model-based applications (front-end and back-end). o Collaborate with software engineers to build scalable and efficient deployment pipelines. Collaboration & Reporting: o Work closely with data scientists, product teams, and engineers to translate business requirements into technical solutions. o Document workflows, model design processes, and technical specifications.