AI Developer, Government

full-time

Posted on: 9/22/2025

Origin: • 🇺🇸 United States

✨ AI Apply

Mid-LevelSenior

ApacheAWSAzureCloudDockerHadoopJavaKubernetesPythonPyTorchScikit-LearnSparkSQLTensorflow

About the role

Design, develop, and train machine learning and deep learning models for various applications, including natural language processing, computer vision, predictive analytics, and recommendation systems.
Preprocess, analyze, and visualize large datasets to extract actionable insights; collaborate with data engineers to ensure data quality and availability.
Integrate AI models into existing software architectures, ensuring seamless functionality and optimal performance.
Stay current with the latest AI research and trends; propose and implement innovative solutions to enhance our AI capabilities.
Work closely with product managers, data scientists, and software engineers to define project requirements and deliver AI-powered solutions.
Develop rigorous testing methodologies to evaluate the performance and reliability of AI systems; troubleshoot and optimize model performance.
Maintain clear and comprehensive documentation of models, experiments, and code for future reference and knowledge sharing.
Ensure that all AI solutions adhere to ethical guidelines, data privacy standards, and regulatory requirements.

Bachelor’s or master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
Proven experience in developing and deploying AI/ML models in a production environment.
Proficiency in programming languages such as Python, Java, or C++.
Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
Familiarity with data processing tools and platforms (e.g., SQL, Apache Spark, Hadoop).
Knowledge of cloud computing services (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes) is a plus.
Hugging Face Ecosystem: Demonstrated experience using Hugging Face tools such as the Transformers library, Datasets, and Tokenizers.
Familiarity with integrating pre-trained models and fine-tuning them for specific applications is highly desirable.
Analytical Skills: Strong problem-solving abilities with a keen attention to detail; ability to work with large datasets and extract meaningful insights.
Communication: Excellent verbal and written communication skills; ability to clearly explain complex technical concepts to non-technical stakeholders.