Machine Learning Engineer

About Us: Lovelace is the only provider of enterprise-scale context engines capable of analyzing trillions of real-time data points to create knowledge graphs that are usable by autonomous agents at the speed, scale, and accuracy required for mission-critical analysis. Lovelace’s context engine platform, Elemental, uniquely integrates data ingestion, entity resolution, and graph building into a single pipeline that empower agentic deployments, delivering 1000X the investigative power for complex queries. With its proprietary ground-breaking YottaGraph, Lovelace provides enterprises with real-time, real-world context, enabling agents to understand the impact of global intelligence on enterprise data for unmatched insights with millisecond precision. Founded in 2023 by Andrew Moore, former head of Google Cloud AI, dean of Carnegie Mellon’s School of Computer Science, and first AI advisor for U.S. CENTCOM, Lovelace currently works with some of the largest public and private enterprises in the world. Job Summary: - 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. Key Responsibilities: - 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. Qualifications: - 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. Benefits: LovelaceAI offers competitive compensation packages, comprehensive benefits. We provide a supportive and inclusive work environment where your skills and expertise can make a significant impact on the safety and security of our communities. Lovelace’s founding team includes: Andrew Moore, who has a track record of building impactful AI systems, designing them with human rights impact assessments as a top priority, leading the AI division of one of the world’s foremost cloud companies, and actively participating in machine learning and AI research over the past two decades. Toby Smith, well known in the Pittsburgh Tech community for his engineering leadership and design skills, and who has led many of the most ambitious and complex system infrastructure projects in Google Pittsburgh and NetApp. Here is a note from Andrew Moore to people who are reading these Job Postings: “Hi folks, I’m so glad you are potentially interested in Lovelace AI. This area means a lot to me because while I am an AI optimist, I also think that we technologists owe it to a rightly skeptical world to show that modern intelligent systems can actually be useful. Usefulness comes in many guises: from life sciences to education and from transportation to entertainment and many others. For many of us, security and public safety is also very high on that list. That reasoning leads to this conclusion: I’m determined to make sure that the people building Lovelace AI gain a lot from the experience, including the chance to solve fascinating problems in computer science, AI, business development, customer success and product management. I also hope that we all learn from each other in a highly enriching work environment. But my main hope is that we have a shared sense of accomplishment as we see an increasing number of national security and public safety domains made safer through sensible and robust use of advanced computer science."