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About Pavo
Pavo is building Enterprise Superintelligence: compounding systems that take ownership of business outcomes and work with humans to deliver them.
We believe that while foundation models are necessary, they are not sufficient. The hard problem is systems intelligence: end-to-end architectures that understand a company's code, data, and decisions, and improve themselves through experience.
We are assembling a small, senior team of researchers and engineers obsessed with systems-first intelligence. Our current team consists of PhDs and ML engineers from top applied ML and coding agent companies, with a heritage of shipping systems at Spotify, ShareChat, and Sourcegraph scale.
Our team has built impressive momentum with a small group of highly capable engineers and researchers.
The Opportunity
This is not a typical applied scientist role. As a Forward Deployed Scientist, you are the crucial link between Pavo's agentic platform and our customers' most challenging applied ML problems.
In a traditional role, you might spend months optimizing a single model for one specific task. At Pavo, our agentic infrastructure acts as a force multiplier, giving you "eight hands" to tackle multiple high-impact problems simultaneously. You will operate like an "Octopus Scientist"—leveraging autonomous agents to execute data cleaning, feature engineering, and model tuning in parallel, allowing you to solve complex applied science challenges at a velocity that would be impossible for a single human researcher.
You will embed with our customers, deeply understand their needs, and use Pavo's platform to build and deploy ML solutions that don't just "work" technically, but drive significant, measurable impact on their key metrics.
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What You'll Do
- Partner with Customers: Work directly with the engineering and product teams of our most strategic customers. You'll be their trusted advisor for all things machine learning, helping them navigate the shift to agentic AI.
- Solve High-Impact Problems: Lead the charge in identifying, scoping, and solving complex business problems using machine learning. This includes everything from improving user engagement and retention to optimizing pricing and inventory.
- End-to-End Model Development: Design, build, and deploy production-grade machine learning models for our customers using the Pavo AI platform, extending its capabilities where necessary.
- Drive Product Strategy: Act as the voice of the customer to our internal product and engineering teams. Your hands-on experience will provide invaluable feedback to shape the future of the Pavo AI platform.
- Quantify and Communicate Impact: Design and run rigorous A/B tests and other experiments to measure the impact of your work. You will be responsible for clearly communicating these results to both technical and non-technical stakeholders.
- Innovate and Research: Stay at the forefront of applied machine learning research to identify new opportunities and techniques that can be leveraged by our customers and integrated into our platform.
What We Are Looking For
We are looking for builders who have seen their models move the needle in the real world.
Core Qualifications
- Experience & Impact: 4+ years of industry experience in a role like Applied Scientist, Machine Learning Engineer, or Research Scientist, with a proven track record of shipping ML-powered products that have moved key business metrics.
- ML & Big Data Stack: Hands-on experience with modern machine learning frameworks (PyTorch, TensorFlow) and large-scale data processing systems (Spark, Hadoop, Beam).
- Communication: Excellent communication skills with the ability to explain complex technical concepts to a variety of audiences, from CTOs to Product Managers.
- Education: A bachelor's degree in Computer Science, Statistics, or a related quantitative field, or equivalent practical experience.
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Preferred Qualifications
- M.S. or Ph.D. in Computer Science, Statistics, or a related quantitative field.
- Expertise in one of the following areas: recommender systems, personalization, search and ranking, computational advertising, causal inference, or reinforcement learning.
- A portfolio of projects or publications in top-tier ML conferences (e.g., KDD, RecSys, SIGIR, WebConf, ICML, ICLR).
- A genuine passion for making complex technology accessible and a desire to help other companies succeed with machine learning.
Why Join Us
- Founding Equity: Significant ownership in a company tackling the next layer of the AI stack.
- Unmatched Variety: Unlike a standard role where you work on one dataset for years, you will encounter the most diverse and challenging datasets in the industry across multiple domains.
- World-Class Team: Collaborate with a dense talent cluster of researchers and engineers who have shipped products serving hundreds of millions of users.
Pavo is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
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