AI/ML Engineer

Open positions

United States

Contract / Contract to full time / Full time

Remote

About the team

At Neural, we are committed to building the future of AI. The world is changing, and we're at the forefront of that transformation. Our team is dedicated to creating innovative solutions that address the unique challenges of today's dynamic industries and unlock the potential of new markets. 

We harness the power of Artificial Intelligence and Machine Learning to drive innovation and create solutions that shape the future of industries. We believe that the future of AI is in your hands. Our mission is to empower individuals and organizations to harness the power of AI to achieve their goals. Join us in shaping the future of AI today

About the position

Neural is seeking an experienced and versatile AI/ML & Foundational Model Engineer to design, train, fine-tune, and deploy large-scale language and multimodal models in support of geospatial, aerospace, and mission-critical decision systems. You will work at the forefront of foundation model development, contributing to our internal LLM stack and supporting capabilities like anomaly detection, autonomous reasoning, and dynamic knowledge graphs.

This is a hands-on engineering role requiring deep knowledge of transformers, NLP, computer vision, and annotation/labelling workflows. You’ll collaborate closely with our product, data, and platform teams to build both generalized and domain-adapted AI systems capable of processing text, code, imagery, and spatial data.

Responsibilities

  • Architect and train transformer-based models, including BERT, GPT, or vision-language hybrids.
  • Build workflows for supervised, unsupervised, and reinforcement learning across NLP and multi-modal tasks.
  • Create high-quality datasets with robust labeling/annotation pipelines.
  • Fine-tune foundation models for specific use cases (e.g., spatial data parsing, technical document summarization).
  • Integrate trained models into production environments via scalable inference services.
  • Monitor performance, perform evaluations, and iterate using continuous feedback loops.
  • Publish internal documentation and contribute to research outputs where appropriate.
  • Work with raster imagery, geospatial data, time series, video, and audio data
  • Integrate databases, vector search, data lakes, and streaming data
  • Build agentic AI applications for geospatial and edge computing

Qualification

  • 3-5+ years of hands-on experience in AI/ML engineering, with a strong portfolio of transformer or LLM-related projects.
  • Proficiency with PyTorch, TensorFlow, Hugging Face, LangChain, or equivalent frameworks.
  • Experience with labeling tools (e.g., Label Studio, Snorkel) and dataset versioning.
  • Strong background in NLP, embeddings, tokenization, attention, and pretraining techniques.
  • Understanding of model optimization techniques (e.g., quantization, distillation, LoRA).
  • Ability to work with cross-functional teams on ML deployment.
  • Experience with computer vision, segmentation, object recognition, and NLP

Preferred

  • Experience with geospatial or Earth observation data.
  • Familiarity with RAG pipelines, vector databases, and multi-agent LLM orchestration.
  • Contributions to open-source LLM projects or relevant academic publications.

Travel

Up to 10%

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