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Agentic AI/ML Engineer, Multimodal

FieldAI· Engineering – Mission, Interaction & Intelligence
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Irvine, CAFull-timePosted 3mo ago

About the role

AI/ML Engineer focusing on Field Foundation Model (FiFM) for multimodal data from autonomous robots, with emphasis on agentic AI, memory, and retrieval-augmented generation. Hybrid of applied research and engineering, from dataset curation to production deployment, solving multimodal perception and insight-generation problems in robotics.

Responsibilities

  • Train and fine-tune million- to billion-parameter multimodal models, with a focus on computer vision, video understanding, and vision-language integration.
  • Track state-of-the-art research, adapt novel algorithms, and integrate them into FiFM.
  • Curate datasets and develop tools to improve model interpretability.
  • Build scalable evaluation pipelines for vision and multimodal models.
  • Contribute to model observability, drift detection, and error classification.
  • Fine-tune and optimize open-source VLMs and multimodal embedding models for efficiency and robustness.
  • Build and optimize Multi-VectorRAG pipelines with vector DBs and knowledge graphs.
  • Create embedding-based memory and retrieval chains with token-efficient chunking strategies.

Qualifications

  • Master’s/Ph.D. in Computer Science, AI/ML, Robotics, or equivalent industry experience.
  • 2+ years of industry experience or relevant publications in CV/ML/AI.
  • Strong expertise in computer vision, video understanding, temporal modeling, and VLMs.
  • Proficiency in Python and PyTorch with production-level coding skills.
  • Experience building pipelines for large-scale video/image datasets.
  • Familiarity with AWS or other cloud platforms for ML training and deployment.
  • Understanding of MLOps best practices (CI/CD, experiment tracking).
  • Hands-on experience fine-tuning open-source multimodal models using HuggingFace, DeepSpeed, vLLM, FSDP, LoRA/QLoRA.
  • Knowledge of precision tradeoffs (FP16, bfloat16, quantization) and multi-GPU optimization.
  • Ability to design scalable evaluation pipelines for vision/VLMs and agent performance.

Skills

Required:Multimodal model training and fine-tuningPythonPyTorchMLOpsOpen-source multimodal models (HuggingFace, DeepSpeed, vLLM, FSDP, LoRA/QLoRA)Vector databases & knowledge graphs (RAG pipelines)Memory and retrieval systems for AI (token-efficient chunking)

Benefits

  • Base pay may vary based on role scope, job-related knowledge, skills, experience, and the Irvine, California market.
Last updated Oct 22, 2026. Interested? Apply on the company site.

About FieldAI

Robot intelligence built for the real-world.

FieldAI is the leader in deploying general-purpose robots in unstructured environments, providing a universal brain that works across many robots, and many tasks.

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