AI Scientist, Platform
Avathon · Pleasanton, California, United States
About this role
## Who We Are & Why Join Us **Avathon** is the leading Industrial AI autonomy platform, helping customers across heavy industries—energy, mining, manufacturing, aerospace, defense, and logistics—accelerate the journey toward autonomous operations. Our platform is built on a **Computational Knowledge Graph** foundation that contextualizes and connects operational data across siloed systems, bringing together time series, structured, unstructured, and machine vision data to power AI-driven applications in: - Asset performance management - Supply chain intelligence - Visual AI - Global trade management With capabilities spanning **digital twins**, **normal behavior modeling**, **natural language processing**, and **computer vision**, Avathon delivers real-time predictive intelligence and agentic decision-making at industrial scale. Learn more: http://avathon.com --- ## Role Overview We are hiring an **AI Scientist** to build the shared AI capabilities of the Avathon platform. Our applications in planning, logistics, PLM, asset performance, and machine vision all rely on the same core: - **Normal Behavior Models** (learn what normal looks like) - **Computational Knowledge Graph** (links industrial data) - **Model Hub** (serves ML and LLM models) - **AI agents** (reason over all of it) You will improve that core so every application gets better at once. This role sits in **Product Engineering**, working with platform engineering to take models from research to production. --- ## You Will ### Core Models - Improve **Normal Behavior Models** and **anomaly detection** for time series and event data across industries - Build methods for **data quality** and **gap filling** on messy industrial sensor and business data - Evaluate and adapt **time series** and **multimodal foundation models** for industrial use ### Knowledge Graph and Agents - 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** so we know when an agent or model is good enough to ship ### Platform and Productization - Work with the **Model Hub** team on model serving, monitoring, retraining, and cost - Package methods as reusable **platform services** that application teams can use without starting from scratch - Write up methods and results clearly for product, customers, and leadership --- ## You’ll Have - **PhD** in Computer Science, Machine Learning, Statistics, or a related field, **or** an **MS with 5+ years** of relevant industry experience - Strong foundation in machine learning, with depth in at least two of: - time series and anomaly detection - knowledge graphs and graph learning - LLMs and agents - Experience building ML/AI capabilities used across many products or customers - Experience at **Palantir, C3 AI, Databricks, Google, AWS, Microsoft**, or an industrial AI company is a strong plus - Strong **Python** and the standard ML stack (**PyTorch**, **Hugging Face**, LLM frameworks) - Experience shipping models to production—not only notebooks - Publications or patents in related areas are a plus --- ## Compensation - **Pay Range:** **$160k - $240k** salary annually (based on factors including geographic location and job-related knowledge, skills, and experience) - **Location:** **Not remote**. Candidates must be based in the **
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