Full-Time
Local Operations Practice Manager
Confirmed live in the last 24 hours
Galileo
51-200 employees
Platform for improving machine learning models
Compensation Overview
$90k - $120k/yr
Senior
Santa Fe, NM, USA
This is an in-person role supporting our New Mexico patient geos.
- 5 years of experience leading teams and operations within a fast-paced clinical environment.
- Strong coaching skills and excitement about helping others build knowledge and expertise.
- Creative problem-solving skills, specifically the ability to immerse in details while organizing work around a high-level vision.
- Understanding of the nuanced needs of local teams and patients.
- Tenacity and positivity, with enthusiasm for motivating oneself and others towards new standards of excellence.
- Partner closely with local clinical leadership to support and grow the team, including direct management and hiring of Health Advocates and Local Mobile Unit Drivers.
- Assume ownership of day-to-day clinic/geo operations and own the performance of the care model and associated KPIs (patient access, patient experience, schedule utilization, local task SLAs, etc.).
- Oversee processes that support core activities and tight execution while building and testing new processes and workflows.
- Problem-solve both in the moment and for the future state, remaining ready to roll up your sleeves to bridge day-to-day gaps and dig into the details.
Galileo offers a platform that helps machine learning teams enhance their models and reduce annotation costs using data-centric algorithms for Natural Language Processing. It allows teams to quickly identify and fix data issues that affect model performance and provides a collaborative space to manage models from raw data to production. Unlike competitors, Galileo integrates easily with existing tools and focuses on actionability, security, and privacy, while also streamlining the data labeling process. The company generates revenue through subscription fees for its services.
Company Size
51-200
Company Stage
Series B
Total Funding
$68.1M
Headquarters
San Francisco, California
Founded
2021
Simplify's Take
What believers are saying
- Integration with NVIDIA NeMo enhances generative AI model performance and reliability.
- AGNTCY's open-source collective positions Galileo as a leader in AI agent interoperability.
- $45M Series B funding boosts Galileo's expansion and technological advancements.
What critics are saying
- Rapid LLM evolution may outpace Galileo's current capabilities, requiring constant updates.
- AGNTCY's industry-standard language could increase competition if Galileo doesn't align.
- Narrowing gap between open-source and proprietary models pressures Galileo to adapt.
What makes Galileo unique
- Galileo integrates quickly with existing tools, enhancing actionability, security, and privacy.
- It offers a collaborative data bench for efficient model tracking and improvement.
- Galileo's platform auto-detects mis-annotated data and supports bulk labeling.
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Benefits
Health Insurance
Dental Insurance
Vision Insurance
Disability Insurance
Parental Leave
Flexible Work Hours
401(k) Retirement Plan
401(k) Company Match
Growth & Insights and Company News
6 month growth
↑ 4%1 year growth
↓ -9%2 year growth
↓ -7%Platform Powers End-to-End Continuous Improvement of Agentic ApplicationsSAN FRANCISCO, March 18, 2025 /PRNewswire/ -- Galileo, the AI Evaluation company, today announced an integration with NVIDIA NeMo ™, enabling customers to continuously improve their custom generative AI models. Now, customers can evaluate models comprehensively across the development lifecycle, curating feedback into datasets that power additional fine-tuning. As a result, customers ship GenAI apps that are more reliable, trusted, and cost-effective.Data Flywheel for AIThe majority of enterprises are developing GenAI applications – including agents and RAG-based chatbots – but it can be challenging to ship and scale these applications due to the non-deterministic outputs of Large Language Models (LLMs). There's even more complexity when AI teams wish to test new LLMs, which are constantly evolving in capability and price point. The solution is to build an AI data flywheel, enabling continuous testing and refinement, collecting data about user interactions for subsequent improvement. When AI teams use data to improve outcomes (whether by fine-tuning, prompt engineering, or in-context learning), they gain a competitive advantage.Galileo and NVIDIA accelerate a data flywheel by collecting and curating better data about the interactions of an AI application
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. One goal for an agentic future is for AI agents from different organizations to freely and seamlessly talk to one another. But getting to that point requires interoperability, and these agents may have been built with different LLMs, data frameworks and code.To achieve interoperability, developers of these agents must agree on how they can communicate with each other. This is a challenging task. A group of companies, including Cisco, LangChain, LlamaIndex, Galileo and Glean, have now created AGNTCY, an open-source collective with the goal of creating an industry-standard agent interoperability language. AGNTCY aims to make it easy for any AI agent to communicate and exchange data with another.Uniting AI Agents“Just like when the cloud and the internet came about and accelerated applications and all social interactions at a global scale, we want to build the Internet of Agents that accelerate all of human work at a global scale,” said Vijoy Pandey, head of Outshift by Cisco, Cisco’s incubation arm, in an interview with VentureBeat. Pandey likened AGNTCY to the advent of the Transmission Control Protocol/Internet Protocol (TCP/IP) and the domain name system (DNS), which helped organize the internet and allowed for interconnections between different computer systems. “The way we are thinking about this problem is that the original internet allowed for humans and servers and web farms to all come together,” he said
When deploying generative artificial intelligence (AI), one of the most fundamental decisions businesses face is whether to choose open-source or proprietary AI models — or aim for a hybrid of the two. “This basic choice between the open source ecosystem and a proprietary setting impacts countless business and technical decision, making it ‘the AI developer’s dilemma,’” according to an Intel Labs blog post. This choice is critical because it affects a company’s AI development, accessibility, security and innovation. Businesses must navigate these options carefully to maximize benefits while mitigating risks
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. Galileo, a San Francisco-based startup, is betting that the future of artificial intelligence depends on trust. Today, the company launched a new product, Agentic Evaluations, to address a growing challenge in the world of AI: making sure the increasingly complex systems known as AI agents actually work as intended.AI agents—autonomous systems that perform multi-step tasks like generating reports or analyzing customer data—are gaining traction across industries. But their rapid adoption raises a crucial question: How can companies verify these systems remain reliable after deployment? Galileo’s CEO, Vikram Chatterji, believes his company has found the answer.“Over the last six to eight months, we started to see some of our customers trying to adopt agentic systems,” said Chatterji in an interview. “Now LLMs can be used as a smart router to pick and choose the right API calls towards actually completing a task
Galileo Technologies Inc., a provider of enterprise AI observability and assessment platforms, today announced that it has raised $45 million in new funding.