---
title: 'Machine Learning Engineer at Lovelace AI'
canonical: 'https://feeny.ai/job/machine-learning-engineer-lovelace-ai-lovelace-hq-pkrd3panewv2'
type: 'job'
last_seen: '2026-09-05'
---

# Machine Learning Engineer at Lovelace AI

- **Company:** Lovelace AI
- **Location:** Lovelace Hq
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2025-10-08
- **Last confirmed live:** 2026-09-05
- **Apply:** https://jobs.ashbyhq.com/lovelace/4fe206c4-c662-4c19-90db-b90e66c27089

## Job description

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."

## About Lovelace AI

## Company Overview
- **One-liner**: Lovelace AI builds enterprise AI infrastructure and context engines to make autonomous agents reliable for mission-critical analysis, primarily serving national security, financial services, and supply chain sectors.
- **Entity Type**: Private (Seed VC stage)
- **Headquarters**: Pittsburgh, Pennsylvania, USA
- **Founded**: 2023
- **Founders**: Andrew Moore, PhD (Co-Founder & CEO); Toby Smith (Co-Founder & Head of Engineering); Jonathan Macoskey (Co-Founder)

## Core Business
- Primary industry/industries: Artificial Intelligence, National Security, Enterprise AI Infrastructure, Financial Services
- Target customers: B2B, Enterprise, Government/Defense agencies, Intelligence community, Financial institutions, Supply chain operators
- Mission or purpose statement: Making autonomous agents work for mission-critical analysis, bringing rigor and accuracy to enterprise AI deployments in industries where bad decisions ruin lives [lovelace.ai](https://lovelace.ai/).

## Products & Services
- **[Elemental — The Context Engine for Enterprise Agents]**: A platform that ingests global data streams in real time and transforms fragmented information into enterprise-specific context engines. It integrates agentic data ops, entity resolution, and graph building into a single end-to-end pipeline at global data scale. Key features include: context built at ingest (not query), full traceability, and defensible outputs for high-stakes decision-making.
- **[Lovelace YottaGraph]**: A continuously maintained world reference graph built from public and commercially available regulatory filings, corporate registries, sanctions lists, news, global movements, and market data. It compresses massive global data into trillions of structured facts with millisecond retrieval, providing global context for agents.
- **Solutions by use case**: National Security Operations Planning, Threat Identification (fusing SIGINT, OSINT, HUMINT), Supply Chain Disruption Monitoring, Enhanced Due Diligence, Cross-border Trade Monitoring, Portfolio Risk Monitoring, Private Wealth Opportunity Monitoring.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: Total Funding — $16.2M (Seed VC round, raised ~1 year ago as of 2025) [cbinsights.com](https://www.cbinsights.com/company/lovelace-ai)
- **Notable Investors/Partners**: RRE Ventures, Magarac Venture Partners, Qudit, NSIN Propel Hawaii Accelerator, xTech Accelerator [cbinsights.com](https://www.cbinsights.com/company/lovelace-ai)
- **Growth Signals**: 
  - The company claims their platform matches Google Gemini Deep Research at less than 1% of the cost [lovelace.ai](https://lovelace.ai/)
  - 19 total employees as of latest data [builtin.com](https://builtin.com/company/lovelace-ai)
  - 3 patents filed, including one on Geospatial moving entity analysis with missing value imputation [cbinsights.com](https://www.cbinsights.com/company/lovelace-ai)
  - CEO holds a high-level advisory role to U.S. CENTCOM for AI, robotics, and autonomous systems

## Competitive Advantages
- **Founder pedigree**: Andrew Moore, PhD, is a globally recognized AI authority — former Dean of Computer Science at Carnegie Mellon University, former Head of Google Cloud AI, and former CENTCOM AI adviser. This gives the company unparalleled credibility and access in the defense and enterprise AI space.
- **Operational-experience convergence**: The team uniquely combines world-class AI engineering with operational leadership drawn from the intelligence community, veterans, the White House Situation Room, NSA, and the Office of the Secretary of Defense [lovelace.ai](https://lovelace.ai/about)
- **Technical moat (YottaGraph)**: The proprietary world reference graph (trillions of structured facts) is a hard-to-replicate data asset that provides global context for agents, with claims of being 100x cheaper than comparable models like Gemini Deep Research.
- **Context-at-ingest architecture**: Unlike standard RAG architectures that build context at query time, Elemental builds context at ingest, enabling deep-research insights with speed and cost efficiency.

## Strategic Focus
- **Current priorities**: Scaling the Elemental platform for enterprise and government clients; deepening capabilities in national security ops, threat identification, and due diligence; reducing the cost of enterprise AI agents while improving accuracy
- **Direction for growth**: Expanding from seed stage into Series A; growing the engineering and forward-deployed teams; targeting more commercial enterprise clients (financial services, supply chain) alongside government contracts

## Why Work Here
- **Culture highlights**: Described as a "serious AI company" with a high bar for hiring — the mission is focused on human safety, conflict zones, disaster response, and deterrence. The team is intentionally small (19 employees) and selective, combining engineers with operational veterans from defense and intelligence.
- **Remote/hybrid/office policy**: **In-Office** — all employees work from the physical Pittsburgh office at 6425 Penn Avenue. Typical time on-site is full-time (on-site workspace) [builtin.com](https://builtin.com/company/lovelace-ai).
- **Notable perks or engineering culture**: 
  - "Our front line is fueled by an entire team of experts who never miss" — emphasizes high ownership and reliability
  - Engineers work on problems at the intersection of AI, financial services, and national security — the work is described as "complex" and requires "the best minds in the world"
  - The team has built foundational infrastructure for Google's core systems, autonomous vehicles, and commercial AI cloud products
  - Patents and published research are encouraged (3 patents filed)

## Sources
1. [lovelace.ai](https://lovelace.ai/) — Official website with product details, team, and mission
2. [lovelace.ai/about](https://lovelace.ai/about) — Company about page with founder bio, team, and investors
3. [jobs.ashbyhq.com/lovelace](https://jobs.ashbyhq.com/lovelace) — Official careers page
4. [cbinsights.com](https://www.cbinsights.com/company/lovelace-ai) — Funding, investors, patents, and headquarters
5. [builtin.com](https://builtin.com/company/lovelace-ai) — Employee count, office policy, culture details

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