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Lovelace AI is building enterprise-scale context engines that analyze trillions of real-time data points to create knowledge graphs for autonomous agents. The company's Elemental platform uniquely integrates data ingestion, entity resolution, and graph building into a single pipeline, delivering 1000X investigative power for complex queries. Founded in 2023 by Andrew Moore (former head of Google Cloud AI and dean of Carnegie Mellon's School of Computer Science), Lovelace works with some of the largest public and private enterprises.
As Staff AI Research Engineer, you will lead the design, development, and deployment of advanced AI models and systems powering Lovelace's context engine and agentic platforms. Day-to-day work includes researching and productionalizing ML models, pipelines, and services in close collaboration with product management and infrastructure engineers.
Key responsibilities:
- Develop core components of the Elemental platform including multimodal data ingestion, entity resolution, knowledge graph construction, and agentic search
- Mentor team members and contribute to technical leadership across the organization
- Collaborate cross-functionally with product and infrastructure groups
- Contribute to externally facing research, technical documentation, and internal best practices
- Design rigorous experiments, interpret results, and communicate technical findings to technical and non-technical stakeholders
This is a full-time, on-site role based in Pittsburgh, PA.
QUALIFICATIONS:
- Strong foundation in Machine Learning and AI Engineering with experience building and scaling production-grade AI systems
- Graduate degree in Computer Science, Machine Learning, or related field, or equivalent practical experience
- Proficiency in ML frameworks (PyTorch or TensorFlow), training pipelines, and deploying/scaling models on Kubernetes-based infrastructure (GPU scheduling, model serving, MLOps tooling)
- Ability to design rigorous experiments, interpret results, and communicate technical findings clearly to both technical and non-technical stakeholders
PREFERRED:
- Advanced expertise in Multimodal ML, NLP, Entity Resolution, Knowledge Graphs, or Agentic Search
- PhD with published research in major ML/NLP conferences (NeurIPS, ICML, ICLR, AAAI, EMNLP, etc.)
- Experience in technical leadership role with mentoring, external stakeholder communication, and cross-functional project management
- Experience bringing products to market and working backwards from customer needs, balancing technical rigor with practical delivery
