Senior AI Engineer

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.

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.

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As a Senior AI Engineer at Avathon, you will play a key role in designing and delivering advanced AI solutions with a strong emphasis on Generative AI and Large Language Models (LLMs). You will apply scientific rigor to develop scalable, production‑ready machine learning systems that drive measurable business impact, working on challenging problems in forecasting, demand planning, renewable energy optimization, anomaly detection, and prescriptive maintenance.

With minimum 5 years of industry experience, you are expected to bring strong expertise in statistical modeling, ML engineering, and modern AI architectures, particularly in GenAI and LLM‑based applications. This role offers the opportunity to work on high‑impact projects that shape next‑generation AI capabilities within the organization.

• Design, develop, and deploy machine learning and Generative AI solutions to solve complex business problems
• Build, fine‑tune, and optimize Large Language Models (LLMs) and transformer‑based architectures for real‑world applications
• Apply rigorous scientific methodologies to experimentation, model evaluation, and performance optimization
• Develop scalable ML pipelines and production‑grade systems in collaboration with Engineering teams
• Conduct prompt engineering, model alignment, evaluation, and performance benchmarking for GenAI applications
• Work closely with Product, Engineering, and Business stakeholders to translate ambiguous requirements into data‑driven AI solutions
• Instrument and monitor LLM applications in production using observability tools, tracking cost, latency, quality, and drift
• Contribute to model governance, responsible AI practices, and performance monitoring in production environments
• Stay current with advancements in Generative AI, LLM research, and applied machine learning, incorporating relevant innovations into company solutions

• Master’s or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field
• Minimum 5 years of hands‑on industry experience in AI engineering, machine learning, data science, or applied AI roles
• Strong experience with Generative AI frameworks and Large Language Models (e.g., transformer architectures, fine‑tuning, RAG systems)
• Proficiency in Python and modern ML/AI libraries such as PyTorch, Tensor Flow, Hugging Face, or equivalent ecosystems
• Solid understanding of statistical modeling, experimentation, and model evaluation methodologies
• Experience building and deploying ML models into production environments
• Familiarity with data engineering workflows and cloud‑based ML platforms (AWS, GCP, or Azure)
• Strong problem‑solving skills with the ability to work independently on complex and ambiguous problem statements
• Excellent communication skills with the ability to present technical insights clearly to cross‑functional stakeholders

• Experience implementing Retrieval‑Augmented Generation (RAG), vector…