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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - **Company:** Lovelace Ai - **Location:** Pittsburgh, United States - **Contract:** Permanent contract - **Skills:** Geographic Information Systems, Artificial Intelligence, Algorithm Design, Amazon Web Services, Artificial Neural Networks, Computer Vision, Microsoft Azure, Distributed Computing Environment, GIS Applications, Graph Database, Intrusion Detection and Prevention, Machine Learning, Natural Language Processing, Software Engineering, Cloud Platform System, Pytorch, Deep Learning, Information Technology, Operational Systems, Machine Learning Operations - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/machine-learning-engineer-lovelace-ai-8290464 ## About the Role * Bachelor's degree in Computer Science, Machine Learning, Data Science, or a related field (Master's or Ph.D. preferred). * Proven experience in machine learning model development, training, and deployment. * Proficiency in software development in familiar ML environments and a willingness to contribute to some new next-gen platforms. * Enthusiasm for analytic methods from fields such as probability theory, statistics, linear algebra and knowledge graphs.. * Familiarity with cloud computing platforms (e.g., AWS, Azure) and distributed computing frameworks. * Excellent problem-solving and analytical skills. * Effective communication skills and the ability to work collaboratively in a team environment. * Must be a US Citizen. Preferred Skills: * Experience with deep learning and neural networks. * Knowledge of geospatial data analysis and GIS tools. * Understanding of ethical and legal considerations in AI and ML. ## Description * As a Machine Learning Engineer, you will play a pivotal role in developing and deploying machine learning models and algorithms to address complex challenges in national security and emergency management. You will both learn a lot and teach a lot as we deal with some of the trickiest problems in the active area between large deep models and fine grained statistical inference., * Algorithm Development: Design, develop, and optimize machine learning algorithms and models for various applications, such as threat detection, image recognition, natural language processing, and predictive analytics. * Efficiency and real-time operations: Work with colleagues to use every tool in the toolboxes of: (1) algorithm design (2) GPU-based optimization and (3) highly performance methodologies such as JAX, XLA, PyTorch. * Model Training and Evaluation: Train, fine-tune, and evaluate machine learning models using appropriate frameworks and tools. Make sure that adaptive systems have hygienic and effective ML Ops. * Deployment and Integration: Implement ML models into operational systems, ensuring seamless integration with existing infrastructure and applications. * Collaboration: Work closely with cross-functional teams, including data scientists, software engineers, domain experts, and government agencies, to develop and implement comprehensive ML solutions. * Security and Compliance: Ensure that all ML solutions meet the highest security and compliance standards, especially when dealing with sensitive data and national security concerns. * Documentation: Create and maintain detailed documentation of machine learning models, code, and processes to facilitate knowledge sharing and future enhancements. * Testing and Validation: Conduct rigorous testing and validation of ML systems to ensure robustness, reliability, and accuracy under various conditions. ## Related Videos - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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