Job description

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, and 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. Cutting-Edge AI Innovation -- Join a team at the forefront of AI, developing groundbreaking solutions that shape the future. High-Growth Environment -- Thrive in a fast-scaling startup where agility, collaboration, and rapid professional growth are the norm. Meaningful Impact -- Work on AI-driven projects that drive real change across industries and improve lives. Learn more at: avathon.com 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 that learn what normal looks like, a Computational Knowledge Graph that links industrial data, a Model Hub that serves ML and LLM models, and AI agents that reason over all of it. You will improve that core so every application gets better at once. This role sits in Product Engineering. You will work 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 or 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. Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience. Location: This role is not remote. Candidates must be based in the Bay Area, CA and are expected to report to our Pleasanton office 5 days a week. Avathon is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws. Avathon is committed to providing reasonable accommodations throughout the recruiting process. If you need a reasonable accommodation, please contact us to discuss how we can assist you.

Requirements

Must-haves

Who We Are & Why Join Us
Learn more at: avathon.com
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
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 or 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

Nice-to-haves

Publications or patents in related areas are a plus

Application prep

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Keywords to mirror

aimlllmmachine learningawspython

Platform: greenhouse
Effort: quick

Benefits

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