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# ML Engineer (Geometric Deep Learning & 3D Vision)

- **Company:** Ririo.Com, Inc.
- **Location:** United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** 3d Models, Airflow, Amazon Web Services, Computer Vision, Microsoft Azure, Cloud Computing, Computer Programming, Data Validation, Data Integrity, Data Mining, DevOps, Python (Programming Language), Metadata, Computational Geometry, Systems Integration, Workflow Management Systems, Data Processing, Data Ingestion, Large Language Models, Multi-Agent Systems, Prompt Engineering, Deep Learning, Information Technology, Feature Extraction, Api Design, Data Pipelines, Docker
- **Published:** May 20, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=65cd06a8af45c2a9

## About the Role

Do you have experience in Prompt engineering?, 3D & Computer Vision

 * Geometric Deep Learning: Proficiency with Open3D, PyTorch3D, or Trimesh for mesh processing and point cloud registration.
 * Spatial Transforms: Deep understanding of Euclidean geometry, 3D coordinate systems, and photogrammetry workflows.

LLMs & Agentic Systems

 * Agentic Frameworks: Experience building autonomous workflows using LangChain, LangGraph, AutoGPT, or CrewAI.
 * Model Integration: Proficiency in prompt engineering and fine-tuning LLMs (OpenAI API, Anthropic, or local models via Ollama/vLLM) for structured data extraction and pipeline decision-making.
 * Vector Databases: Experience with Pinecone, Milvus, or Weaviate for managing spatial embeddings and metadata.

Data Pipelines & DevOps

 * Orchestration Tools: Expertise in building and monitoring pipelines using Dagster, Prefect, or Apache Airflow.
 * Data Validation: Experience with Great Expectations or Pydantic to ensure data integrity across the "whole flow."
 * Cloud Infrastructure: Familiarity with deploying ML workloads on AWS, GCP, or Azure using Docker and Kubernetes.

 * Experience building "Human-in-the-loop" systems where LLMs handle the edge cases of 3D data processing.
 * Background in Computational Geometry combined with modern LLM-Ops.
 * A proven track record of automating complex, multi-step engineering workflows.
 * Strong programming skills in Python is a must.
 * Bachelor's/Master's degree in Computer Science/ Engineering or a related field.

## Description

*
3D Registration & Alignment: Develop pipelines to align 3D meshes (photogrammetry) with CAD models using high-precision spatial transforms.

 * Agentic Pipeline Orchestration: Build autonomous agents to manage the "whole flow"-from data ingestion and scale correction (mm vs. meters) to final metric validation.
 * Data Integrity & Remediation: Architect automated systems to detect and correct common data pipeline failures, such as coordinate system mismatches, scale discrepancies (mm vs. meters), and metadata mislabeling.
 * Closed-Loop Validation: Integrate alignment metrics directly into the ML inference flow, ensuring the model provides a confidence score or "alignment success" rating post-run.
 * Spatial Feature Extraction: Extract actionable insights from the "whole flow" of provided data to optimize placement and interaction between objects.


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