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
The Opportunity
We are looking for exceptional new computer science graduates who are builders at heart, writing software, conducting research, building ambitious projects, or pushing technology beyond what they've learned in the classroom. As an Associate AI Engineer, you will join Avathon's AI Engineering team and work alongside AI researchers, applied scientists, and engineers to build the intelligence behind our Physical AI platform. You will work on hard technical problems spanning agentic AI, machine learning, reasoning, knowledge graphs, multimodal AI, time-series intelligence, optimization, and autonomous decision‑making.
What You'll Work On
- Build physical AI: Develop intelligent systems that can understand complex operating environments, reason over real-world context, predict what happens next, and determine what actions should be taken
- Build AI agents: Develop and evaluate agentic systems capable of reasoning, planning, using tools, interacting with enterprise and operational systems, and executing multi-step workflows
- Advance machine intelligence: Build models and algorithms across prediction, anomaly detection, forecasting, classification, optimization, recommendation, and decision intelligence
- Build knowledge & reasoning systems: Work with Avathon's computational knowledge graph to give AI an understanding of relationships across assets, processes, materials, suppliers, operations, and complex industrial systems
- Explore multimodal AI: Apply LLMs, vision models, time-series models, retrieval, and multimodal techniques across sensor signals, documents, images, video, engineering information, and enterprise data
- Develop autonomous decision systems: Help move AI beyond prediction toward reasoning, prescription, optimization, planning, and increasingly autonomous action
- Take AI from research to production: Turn promising algorithms, models, and prototypes into reliable, scalable AI systems capable of operating against large and complex real-world datasets
- Experiment at the frontier: Rapidly prototype and evaluate emerging AI architectures, models, and techniques and determine where they can create meaningful advantages within Avathon's platform
- Engineer for the real world: Solve challenges involving scale, latency, reliability, model performance, explainability, and deployment where AI outputs can influence real operational decisions
- Own real problems early: Work alongside Product and Forward Engineering teams on difficult customer and platform problems, with meaningful technical ownership from the start of your career
What We're Looking For:
- Bachelor's degree in computer science from a leading computer science and engineering university; graduating in 2027
- Strong academic achievement, with a cumulative undergraduate GPA of 3.6 or higher required
- No prior full-time professional experience required
- Exceptional foundation in algorithms, data structures, software engineering, probability, statistics, linear algebra, and computer science fundamentals
- Strong programming ability, particularly in Python, with the ability to write high-quality, maintainable software
- Strong understanding of machine learning and modern AI fundamentals, developed through coursework, research, internships, independent projects, or hands‑on experimentation
- Experience or demonstrated interest in areas such as LLMs, deep learning, agentic AI, computer vision, NLP, reinforcement learning, optimization, knowledge graphs, robotics, or autonomous systems
- Familiarity with modern AI/ML frameworks and a demonstrated ability to rapidly learn new models, tools, and technical concepts
- Evidence that you build beyond the classroom through research, technically ambitious personal projects,