FieldAI

6 Jobs

120 Employees

About the Company

FieldAI is pioneering the development of a field-proven, hardware agnostic brain technology that enables many different types of robots to operate autonomously in hazardous, offroad, and potentially harsh industrial settings - all without GPS, maps, or any pre-programmed routes.

Listed Jobs

Company Name: FieldAI
Job Title: Agentic AI/ML Engineer - Multimodal
Job Description: Job title: Agentic AI/ML Engineer - Multimodal Role Summary: Develop agentic AI and multimodal models (vision, vision-language, time-series) to transform autonomous robot data into actionable insights, focusing on scalable model development, optimization, and deployment. Expactations: Full-cycle ML role requiring applied research, engineering, and rapid iteration on multimodal models (CV, video, VLMs) with deployment to production, alongside contributions to broader perception/insight systems. Key Responsibilities: - Train/finetune large-scale multimodal models (millions-billions of parameters) - Integrate state-of-the-art algorithms and optimize for efficiency/robustness - Design datasets, evaluation pipelines, and interpretability tools - Implement RAG pipelines using vector DBs and knowledge graphs - Optimize multi-GPU inference, quantization (int4/int8), and memory-efficient architectures - Build scalable drift detection, error analysis, and drift mitigation systems - Develop agent memory/retrieval chains and temporal-spatial modeling solutions Required Skills: - Computer vision, video understanding, multimodal scene analysis - Python/PyTorch with production-level proficiency - MLOps (CI/CD, experiment tracking, cloud infrastructure) - Open-source VLMs (HuggingFace, DeepSpeed, vLLM, FSDP) - Model optimization (FP16/bfloat16, quantization, distillation) - Temporal modeling, zero/few-shot learning, open-vocabulary detection Required Education & Certifications: Master’s/Ph.D. in Computer Science, AI/ML, or equivalent; 2+ years industry CV/ML/AI experience or relevant publications.

Irvine, United states

On site

Junior

27-09-2025

Company Name: FieldAI
Job Title: 1.78 Robotics Graduate Research Internship – Robot Learning - Pittsburgh
Job Description: **Job Title** Robotics Graduate Research Internship – Robot Learning **Role Summary** Graduate intern (MS or PhD) develops advanced robot learning techniques, adapts large‑scale foundation models to robotic tasks, and validates research on physical robots. Works with research and engineering teams to design experiments, run distributed training pipelines, and contribute to publishable outcomes. **Expectations** - Deliver original research contributions in skill learning, reinforcement or imitation learning, and foundation model adaptation. - Design and execute experiments on simulations and real‑world robotic platforms, including manipulators, mobile robots, and field‑deployed systems. - Publish papers or workshop submissions to top venues (CoRL, ICRA, NeurIPS, ICML, CVPR). - Contribute code to open‑source robotics or AI projects and maintain robust, reproducible pipelines. - Engage in cross‑disciplinary collaboration and communicate results to both technical and non‑technical stakeholders. **Key Responsibilities** 1. Conduct research on transferable skill learning across diverse robot embodiments. 2. Adapt vision‑language models (VLMs) and large language models (LLMs) for perception, reasoning, and control in robotics. 3. Design, deploy, and scale large‑scale training pipelines using PyTorch and distributed systems. 4. Perform sim‑to‑real transfer studies, domain adaptation, and scaling‑law experiments. 5. Validate trained models on real robots, addressing challenges in traversability, locomotion, and dexterous manipulation. 6. Collaborate with peers to prepare manuscripts, posters, and code releases for conferences and journals. **Required Skills** - Proficiency in Python programming and ML frameworks (PyTorch preferred). - Strong foundation in machine learning theory, reinforcement learning, imitation learning, or foundation models. - Experience with experimental design, statistical analysis, and rapid iteration on research ideas. - Familiarity with ROS/ROS2 or equivalent robot middleware. - Ability to work with distributed training and high‑performance computing resources. - Knowledge of perception pipelines (3D vision, mapping, traversability) or manipulation systems is a plus. **Required Education & Certifications** - Current enrollment as a Master’s or Ph.D. student in Robotics, Computer Science, AI/ML, or a closely related field. - Evidence of prior research experience or publications in robotics/AI conferences is highly desirable.

Pittsburgh, United states

On site

Junior

30-09-2025

Company Name: FieldAI
Job Title: 1.12 Senior AI Software Engineer — Edge Model Optimization & Deployment
Job Description

Seattle, United states

Hybrid

Senior

19-10-2025

Company Name: FieldAI
Job Title: 1.62 Machine learning Engineer
Job Description: Job Title: Machine Learning Engineer Role Summary: Design, train, and deploy advanced machine learning models for autonomous robot perception, planning, and decision‑making. Drive end‑to‑end learning pipelines that generalize across diverse environments, ensuring reliable deployment, continuous monitoring, and automated retraining of models in production. Expectations: - Deliver scalable, high‑performance models that improve navigation, planning, and manipulation for autonomous robots. - Reduce model drift and maintain performance through automated monitoring and retraining workflows. - Collaborate cross‑functionally with scientists, software engineers, and robotics experts to advance model architecture and training methodologies. Key Responsibilities: - Architect and implement deep learning pipelines (transformers, CNNs) for navigation and decision‑making. - Apply imitation learning and reinforcement learning to enhance robot planning and reasoning. - Develop data generation and collection strategies to enrich training datasets. - Deploy models into production environments, including edge‑device integration. - Monitor deployed models, detect drift, and trigger automated retraining as needed. - Troubleshoot deployment, performance, and integration issues across robotics systems. Required Skills: - Proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, JAX). - Deep understanding of contemporary deep learning architectures, optimization, and evaluation techniques. - Hands‑on experience deploying ML models for robotics, autonomous vehicles, or NLP in production. - Expertise in imitation learning and reinforcement learning. - Working knowledge of C++ for deployment and system integration. - Strong analytical skills and ability to translate research advances into production solutions. Required Education & Certifications: - Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Statistics, or related field. - Relevant certifications in machine learning, deep learning, or robotics (preferred but not mandatory).

Irvine, United states

On site

31-10-2025

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