Generative AI Lead / Senior Machine Learning Engineer

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About Taiyō.AI

Taiyō.AI is the first vertical AI platform purpose-built for the global infrastructure ecosystem—construction firms, engineering companies, suppliers, insurers, investors, and governments shaping the built environment.

We integrate project & procurement data, geospatial layers, supply networks, operational records, market intelligence, and technical documentation into an intelligent cognitive layer that allows organizations to see projects, risks, and opportunities with unprecedented clarity.

Our platform includes:

• Enterprise knowledge graph and data mesh spanning millions of infrastructure records globally
• Generative AI agents for strategic insights, risk discovery, and project planning
• Custom LLM fine-tuning and evaluation for real-world enterprise workflows
• Multimodal interfaces supporting geospatial, document, chat, and structured data workflows

We are a global team operating at the intersection of AI systems, economics, infrastructure delivery, and organizational decision-making.

Role Overview

Generative AI Lead

This is a foundational role. You will shape the technical direction of our AI stack and help move the industry from intuition and legacy data systems to measurable cognitive intelligence.

Key Responsibilities

Modeling & Systems Engineering

• Lead design and implementation of custom fine-tuning, RAG pipelines, embeddings, vector stores, and model evaluation frameworks.
• Build and optimize knowledge graph + generative retrieval pipelines that operate across highly heterogeneous data modalities.
• Evaluate trade-offs between open-weight models (LLaMA, Mistral, Qwen, etc.) and frontier API-based models.
• Develop scalable inference and caching strategies (vLLM, GGUF, quantization, distributed inference).

Multimodal & Dataset Engineering

• Work across text, tabular, geospatial, PDF/document, and image/plan drawing modalities.
• Construct large-scale curated datasets for supervised fine-tuning, preference tuning, and reward modeling.
• Design automatic data labeling, embedding clustering, and synthetic data generation pipelines.

Evaluation & Reliability

• Develop quantitative evaluation benchmarks for reasoning quality, hallucination resistance, retrieval accuracy, and domain precision.
• Support “reliability engineering” approaches for production AI — fallback logic, uncertainty scoring, confidence calibration.

Cross-Functional Collaboration

• Work closely with product, customer success, and domain experts (infrastructure, economics, construction planning).
• Translate complex workflows into agentic task orchestration systems that deliver real business outcomes.

Qualifications

Required

• Strong programming background (Python, PyTorch, JAX or TensorFlow).
• Deep familiarity with LLM fine-tuning, embeddings, RAG, vector databases, and LLMOps workflows.
• Strong understanding of machine learning theory: probability, optimization, statistical learning, and empirical evaluation.
• Experience shipping production ML systems (not only research prototypes).

Preferred

• Experience with geospatial data, document intelligence, or enterprise knowledge systems.
• Familiarity with distributed systems, GPUs, training pipelines, and memory optimization.
• Experience in infrastructure, engineering, supply chain, or real-asset domains (not required, but valuable methodologically).

Nice to Have

• Knowledge of agent-based planning, reasoning models, chain-of-thought alignment, RLHF, DPO, or model distillation.
• Experience working with American and/or global enterprise customer expectations.

What We Value

• Depth + clarity of thought
• Intellectual honesty and precision
• Ability to move from research → prototype → production
• Curiosity about how society builds, finances, and maintains infrastructure
• Comfort in ambiguity; bias toward outcome and simplicity

Growth & Opportunity

• Lead and scale the AI team as we expand.
• Shape a new class of cognitive systems for real-world industries.
• Work directly with founders, researchers, and global industry leaders.
• Influence product strategy, research direction, and system architecture at a foundational level.

Compensation

• Competitive salary based on experience
• Meaningful equity participation
• Remote-friendly with periodic global travel opportunities (US / EU / India / Middle East)