AI Scientist, Platform

Avathon•Pleasanton, CA

4d•$160,000 - $240,000•Onsite

About The Position

Avathon is hiring an AI Scientist to build and improve shared AI capabilities used across its industrial AI platform and applications in planning, logistics, product lifecycle management, asset performance, and machine vision. The role is in Product Engineering and works with platform engineering to bring models from research into production. The position focuses on Normal Behavior Models and anomaly detection, data quality and gap filling, adapting time-series and multimodal foundation models, and methods for discovering ontologies, resolving entities, and mapping raw data into a Computational Knowledge Graph. It also involves building and evaluating AI agents that query the graph, call models, and recommend actions with clear guardrails and human approval, as well as designing evaluation frameworks for deciding when models and agents are ready to ship. The AI Scientist will collaborate with the Model Hub team on model serving, monitoring, retraining, and cost; package methods as reusable platform services; and communicate methods and results clearly to product teams, customers, and leadership. The role is based in Pleasanton, California, and requires working from the office five days a week.

Requirements

PhD in Computer Science, Machine Learning, Statistics, or a related field, or an MS with at least five years of relevant industry experience.
Strong foundation in machine learning, with depth in at least two of the following: time series and anomaly detection; knowledge graphs and graph learning; LLMs and agents.
Experience building ML or AI capabilities used across many products or customers.
Strong Python skills and experience with the standard ML stack, including PyTorch, Hugging Face, and LLM frameworks.
Experience shipping models to production, not only working in notebooks.
Must be based in the Bay Area, California, and report to the Pleasanton office five days a week.

Nice To Haves

Experience at Palantir, C3 AI, Databricks, Google, AWS, Microsoft, or an industrial AI company.
Publications or patents in related areas.

Responsibilities

Improve Normal Behavior Models and anomaly detection for time-series and event data across industries.
Build methods for data quality and gap filling on industrial sensor and business data.
Evaluate and adapt time-series and multimodal foundation models for industrial use.
Build methods for ontology discovery, entity resolution, and mapping raw data into the knowledge graph.
Build and evaluate AI agents that query the graph, call models, and recommend actions with clear guardrails and human approval.
Design evaluation frameworks to determine when an agent or model is ready to ship.
Work with the Model Hub team on model serving, monitoring, retraining, and cost.
Package methods as reusable platform services for application teams.
Write up methods and results clearly for product, customers, and leadership.
Work with platform engineering to take models from research to production.