Extend what is possible with Lumafield’s agentic tools by working across the agent stack, from top level harness and eval development down to fine-tuning and pre-training of foundational encoders for spatial reasoning.
Compensation
Lumafield offers both competitive cash and equity compensation, as well as a health & wellness stipend, 401k, parental leave, flexible PTO, commuter benefits, company wide events and more!
Responsibilities
Benchmark local LLMs, VLMs, and perception encoders
Fine tune and post-train models on domain-specific data and tasks
Develop harnesses and build real, deployed agents that our customers use
Develop evaluations that predict real world agent performance accurately
Partner with product and engineering to continually improve agents and agentic workflows
Requirements
Advanced degree in machine learning, optimization, or a relevant discipline
Lead the application and cognitive layer of humanoid robots, building voice and multimodal AI applications, orchestrating robotic behaviors, and integrating cloud and edge services.
Compensation
Salary range $107,000 - $172,000 USD. It is not typical for offers to be made at or near the top of the range. The actual salary will be determined based on experience and other job-related factors.
Responsibilities
Implement high-level application software, interaction workflows, and robotic behavioral state machines
Translate human speech, gestures, environmental cues, and contextual information into deterministic robotic tasks
Integrate vision pipelines, object detection, scene understanding, spatial tracking, and voice interactions
Design and develop advanced AI algorithms for next-generation video analytics, leveraging modern AI models and architectures to solve complex video understanding challenges.
Responsibilities
Research and explore state-of-the-art AI models, Computer Vision techniques, and emerging technologies to identify new opportunities for advancing video analytics capabilities.
Develop algorithms and solutions for challenging video analytics and video understanding problems, leveraging Computer Vision, deep learning, LLMs, VLMs, and other relevant AI technologies.
Experiment and evaluate different models, algorithms, and approaches, build proof-of-concepts, and assess their performance and suitability for real-world applications.
Integrate algorithms and AI models into existing software systems, collaborating with software engineers to deliver complete product capabilities.
Optimize algorithms and model inference for performance, accuracy, and resource utilization, meeting production requirements and hardware constraints.
Requirements
Master's degree in Computer Science, mathematics, EE or a related field
Lead end-to-end delivery of all IT workstreams for the new warehouse facility.
Compensation
The pay range for this position is $70.00 - $88.00/hr.
Responsibilities
Lead end-to-end delivery of all IT workstreams for the new warehouse facility.
Manage project scope, schedule, risks, dependencies, and governance.
Coordinate SAP EWM implementation and integration with warehouse automation systems.
Lead infrastructure deployment activities including network and wireless infrastructure, MDF/IDF room setup, structured cabling and fiber installation, server, rack, and endpoint deployment, warehouse RF coverage and device readiness.
Coordinate deployment and integration of VLMs, conveyors, sortation systems, autonomous mobile robots, RFID solutions, WES/WCS platforms.
Requirements
Bachelor's degree in Information Technology, Engineering, Supply Chain, or related field.
Internship focused on developing and deploying Generative AI models for SAS customers.
Compensation
Hourly rates for SAS internships are based on an applicant’s year in school and the role they are hired into. Rates range from $15 to $30 per hour for associate and bachelor’s-level positions and from $29 to $49 per hour for master’s and Ph.D positions. Internship roles are not eligible for bonuses.
Responsibilities
Build Generative AI models to solve the challenges of SAS customers using large language models (LLMs) and/or visual language models (VLMs).
Use libraries like LangChain, LangSmith etc. to build applications leveraging LLMs and VLMs.
Collaborate with data scientists and assist in prompt engineering, Retrieval-Augmented Generation (RAG) workflow to solve the business problems of SAS customers.
Research and develop high-quality demos to illustrate the application of Generative AI in solving practical problems.
Optimize the deployment pipeline for Generative AI models.
Requirements
Master's or PhD
Computer Science
Electrical Engineering
Nice to have: Experience developing and deploying Large Language models (LLMs)
Nice to have: Experience with practical implementations of LLMs and advanced analytics projects
Lead the Safety AI team to build end-to-end computer vision and machine learning for Samsara’s AI dash cameras, driving real-time driver safety insights and in-cab alerts.
Compensation
$178,640—$287,100 USD
Responsibilities
Drive the Safety AI Platform Architecture
Own the technical direction for Samsara's on-device and cloud safety AI systems
Lead the transition from individual model deployments to a coherent, system-level platform
Evaluate and integrate emerging AI capabilities
Partner with product and full-stack teams to define, scope, and ship safety features
Requirements
MS or PhD in Computer Science, Electrical Engineering, or a related technical field
Nice to have: background in autonomous vehicles
Nice to have: robotics
Nice to have: fleet telematics
Nice to have: experience with safety and reliability in production
Lead the technical implementation and architecture of advanced robotic systems, translating complex algorithms into reliable, production-ready hardware and software solutions.
Locations (2)
Sunnyvale, California, United States
Pittsburgh, Pennsylvania, United States
Compensation
The U.S. base salary range for this full-time position in Sunnyvale, California is $330,000-$350,000.
Responsibilities
Lead end-to-end robotics deployment from concept to real-world operating environments
Define and drive long-term robotics research roadmap
Make key decisions on system architecture, hardware-software co-design, and make-or-buy strategies
Foster agile and pragmatic engineering culture within interdisciplinary teams
Mentor and coach researchers across mechanical engineering, electronics, software engineering, and AI
Requirements
Master's degree in Robotics, Mechatronics, Computer Science, Electrical Engineering or equivalent
The AI Foundations team focuses on bringing the vision for AI at Capital One to life, covering the entire research life cycle from academic partnerships to building production systems.
Locations (4)
New York, New York, United States
Cambridge, Massachusetts, United States
McLean, Virginia, United States
San Jose, California, United States
Compensation
Cambridge, MA: $218,700 - $249,600; McLean, VA: $218,700 - $249,600; New York, NY: $238,700 - $272,300; San Jose, CA: $238,700 - $272,300
Responsibilities
Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money.
Intern - Software Engineer, Spatial AI Agent Platform
Huawei Research Center Germany · Posted Nov 4, 2026
Internship focused on building the Spatial AI Agent Platform, combining software architecture, design, implementation, and research of AI agent technologies.
Responsibilities
Define and develop software architecture
Research and evaluate emerging architectures and technologies
Evaluate and improve system quality
Create end-to-end demonstrations
Requirements
Master’s program in Computer Science, Software Engineering, Artificial Intelligence, Electrical Engineering or related field
Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, and more — to reveal the insights hidden within huge volumes of numeric and textual data.
Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation.
Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences.
Flex your interpersonal skills to translate the complexity of your work into tangible business goals.
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