Job Specifications
Who are We?
Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications. Learn more at https://fieldai.com.
About the Job
Our Field Foundation Model (FFM) powers a global fleet of autonomous robots that capture massive streams of multimodal data across diverse, dynamic environments every day. As part of the Insight Team our mission is to transform this raw, multimodal data into actionable insights that empower our customers and engineers to deliver value. Field-insight Foundation Model (FiFM) is at the core of how we transform multimodal data from autonomous robots into actionable insights. As an AI/ML Engineer on the FiFM team, you will drive research and model development for one of Field AI's most ambitious initiatives. Your work will span computer vision, vision-language models (VLMs), multimodal scene understanding, and long-memory video analysis and search, with a strong emphasis on agentic AI (tool use, memory, multimodal retrieval-augmented generation).This is a full-cycle ML role: you'll curate datasets, fine-tune and evaluate models, optimize inference, and deploy them into production. It's a blend of applied research and engineering, requiring creativity, rapid experimentation, and rigorous problem-solving. While FiFM is your primary focus, you'll also contribute to broader perception and insight-generation initiatives across Field AI.
What You'll Get To Do:
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
What You Have:
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
The Extras That Set You Apart:
Experience with Agentic/RAG pipelines and knowledge graphs (LangChain, LangGraph, LlamaIndex, OpenSearch, FAISS, Pinecone)
Familiarity with agent operations logging and evaluation frameworks
Background in optimization: token cost reduction, chunking strategies, reranking, and retrieval latency tuning
Experience deploying models under quantized (int4/int8) and distributed multi-GPU inference
Exposure to open-vocabulary detection, zero/few-shot learning, multimodal RAG
Knowledge of temporal-spatial modeling (event/scene graphs)
Experience deploying AI in edge or resource-constrained environments
Compensation and Benefits
Our salary range is generous ($70,000 - $200,000 annual), but we take into consideration an individual's background and experience in determining final salary; base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience. Also, while we enjoy being together on-site, we are open to exploring a hybrid or remote option.
Why Join Field AI?
We are solving one of the world's most complex challenges: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models(tm) set a new standard in perception, planning, localization, and manipulation, ensuring our approach is explainable and safe for deployment.
You will have the opportunity to work with a world-class team that thrives on creativity, resilience, and bold thinking. With a decade-long track record of deploying solutions in the field, winning DARPA challenge segments, and bringing expertise from org