This fellowship is designed for a researcher at the intersection of industry-scale data and academic rigor. The role involves leading research at the forefront of Document Understanding, designing and implementing AI-Native agentic systems to unlock insights from billions of historical and genealogical records.
Responsibilities
Innovate with State-of-the-Art AI for tasks such as OCR/HTR, transcription, Named Entity Recognition (NER), Relation Extraction (RE), Coreference Resolution, Summarization, and Knowledge Graphs.
Design and implement multi-agent workflows using frameworks like LangChain, LangGraph, CrewAI, AutoGen, AgentCore, Strands, Google ADK, A2A.
Evaluate the performance of multi-modal AI & LLMs such as GPT, Gemini, Claude, Llama, and Qwen for zero-shot and few-shot scenarios.
Responsible for algorithm modeling, analysis, and implementation for ZEISS products, encompassing both 2D and 3D imaging solutions, as well as related imaging technologies.
Responsibilities
Responsible for the CT/Xray image algorithm modeling, analysis, and implementation
Responsible for the core technical issue solving and optimization
Responsible for the cross-site technical alignment
Work with team to build and drive the tech stack development
Develop advanced imaging and computational solutions for next-generation eBeam inspection systems.
Compensation
Base Pay Range: $186,200.00 - $316,500.00
Responsibilities
Collaborate with electron optics and systems engineering teams to model SEM image formation and understand imaging performance, aberrations, and other physical effects.
Develop advanced image restoration and defect detection algorithms for low signal-to-noise SEM imaging.
Apply computer vision, image processing, deep learning, and physics-guided modeling techniques to semiconductor inspection challenges.
Design and develop digital twin and synthetic SEM simulation capabilities for internal data generation, modeling, and experimentation.
Partner with applications teams and customers to understand semiconductor manufacturing processes, including lithography, etch, and deposition, and their impact on SEM imaging.
Requirements
Master's degree or Ph.D. in Computer Science, Electrical Engineering, Physics, Applied Physics, Applied Mathematics, Optical Engineering, or a related technical discipline.
Develop and maintain desktop, embedded, and cloud applications for industrial imaging solutions, including 3D data analysis, rendering, image processing, and cloud services.
Compensation
For non-senior engineers, we anticipate paying $100,000 to $150,000 per year.
Responsibilities
Develop a 3D data analysis desktop visualization application
Develop rendering and image processing algorithms using Nvidia CUDA
Develop data capture and control software for field engineers
Develop new features for ultrasonic imaging embedded systems
Develop database components for tracking and analysis
The Hivemind Solutions Perception team develops the next generation of perception capabilities for autonomous systems by combining state-of-the-art machine learning with the proven foundations of computer vision.
Compensation
Pay within range listed + Bonus + Benefits + Equity
Responsibilities
Design, train, fine-tune, and maintain state-of-the-art vision, vision-language, and vision-language-action models that improve perception and decision-making for autonomous systems.
Build scalable data pipelines, supervised fine-tuning (SFT) workflows, and evaluation loops that continuously improve model performance on mission-relevant tasks.
Deploy and optimize machine learning models for embedded hardware using technologies such as ONNX, TensorRT, and hardware-accelerated inference frameworks.
Apply modern machine learning techniques to solve challenging perception and autonomy problems across aerial and other autonomous systems operating in complex, real-world environments.
Translate cutting-edge machine learning research into production-ready capabilities by balancing model performance, robustness, computational efficiency, and operational reliability.
Requirements
Bachelor’s degree
Master’s degree
PhD
Nice to have: autonomous systems for defense customers
Nice to have: vision-language models
Skills
Staff Software Engineer, Perception (R5421)
f7d8749a-72d6-407c-bf98-292ea630c73a · Posted Oct 16, 2026
The Hivemind Solutions Perception team develops the next generation of perception capabilities for autonomous systems, focusing on autonomy software, aircraft, and synthetic reality technologies.
Compensation
Pay within range listed + Bonus + Benefits + Equity
Responsibilities
Develop the next generation of perception capabilities for autonomous systems
Design, train, and fine-tune vision-language (VLM) and vision-language-action (VLA) models
Build scalable machine learning pipelines and evaluation frameworks
Deploy and optimize ML models using TensorRT and ONNX
Partner with research, autonomy, and platform teams to translate research into production
Requirements
Typically requires 7 years of experience with a Bachelor’s degree
6 years and a Master’s degree
4 years with a PhD
Nice to have: Experience with autonomous systems for defense customers
Nice to have: Experience with vision-language models, vision-language-action models, and world models
Develop and implement machine learning models to improve the realism of simulated sensor data, including for example approximation of light transport, material models, 3D representation and black box sensor characterization.
Develop content generation systems for creating diverse and realistic simulation scenarios, including perception signals from geospatial data, measurements from novel hardware, and structured and unstructured text conditioning.
Create behavior models for various actors in simulations such as pedestrians, vehicles, drones.
Design and implement reinforcement learning algorithms for training robotic systems within the simulation environment.
Optimize ML model performance for simulation applications, including low latency inference, architectural improvements and model compression.
Requirements
Master's or PhD in a relevant field (e.g. computer science, mechanical engineering, physics, math, robotics, etc.) or equivalent working experience.
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